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How Candidate Screening Tools Can Build 30+ ATS Integrations in Two Days

Looking to scale your ATS integrations faster and with less resources? Read this article to see how a unified ATS API can help your use case

If you want to unlock 40+ HRIS and ATS integrations with a single API key, check out Knit API

With the rise of data-driven recruitment, it is imperative for each recruitment tool, including candidate sourcing and screening tools, to integrate with Applicant Tracking Systems (ATS) for enabling centralized data management for end users. 

However, there are hundreds of ATS applications available in the market today. To integrate with each one of these applications with different ATS APIs is next to impossible. 

That is why more and more recruitment tools are looking for a better (and faster) way to scale their ATS integrations. Unified ATS APIs are one such cost-effective solution that can cut down your integration building and maintenance time by 80%. 

Before moving on to how companies can leverage unified ATS API to streamline candidate sourcing and screening, let’s look at the workflow and how ATS API helps. 

Candidate sourcing and screening workflow

Here’s a quick snapshot of the candidate sourcing and screening workflow: 

1) Job posting/ data entry from job boards

Posting job requirements/ details about open positions to create widespread outreach about the roles you are hiring for. 

2) Candidate sourcing from different platforms/ referrals

Collecting and fetching candidate profiles/ resumes from different platforms—job sites, social media, referrals—to create a pool of potential candidates for the open positions.

3) Resume parsing 

Taking out all relevant data—skills, relevant experience, expected salary, etc. —from a candidate’s resume and updating it based on the company’s requirement in a specific format.

4) Profile screening

Eliminating profiles which are not relevant for the role by mapping profiles to the job requirements.  

5) Background checks 

Conducting a preliminary check to ensure there are no immediate red flags. 

6) Assessment, testing, interviews

Setting up and administering assessments, setting up interviews to ensure role suitability and collating evaluation for final decision making. 

7) Selection 

Sharing feedback and evaluation, communicating decisions to the candidates and continuing the process in case the position doesn’t close. 

How ATS API helps streamline candidate sourcing and screening

Here are some of the top use cases of how ATS API can help streamline candidate sourcing and screening.

Centralized data management and communication

All candidate details from all job boards and portals can be automatically collected and stored at one centralized place for communication and processing and future leverage. 

Automated profile import

ATS APIs ensure real time, automated candidate profile import, reducing manual data entry errors and risk of duplication. 

Customize screening workflows 

ATS APIs can help automate screening workflows by automating resume parsing and screening as well as ensuring that once a step like background checks is complete, assessments and then interview set up are triggered automatically. 

Automated candidate updates within the ATS in real time

ATS APIs facilitate real time data sync and event-based triggers between different applications to ensure that all candidate information available with the company is always up to date and all application updates are captured ASAP.  

Candidate engagement data, insights and patterns using ATS data

ATS APIs help analyze and draw insights from ATS engagement data — like application rate, response to job postings, interview scheduling — to finetune future screening.

Integrations with assessment, interview scheduling and onboarding applications

ATS API can further integrate with other assessment, interview scheduling and onboarding applications enabling faster movement of candidates across different  recruitment stages. 

Personalized outreach based on historical ATS data

ATS API integrations can help companies with automated, personalized and targeted outreach and candidate communication to improve candidate engagement, improve hiring efficiency and facilitate better employer branding. 

Undoubtedly, using ATS API integration can effectively streamline the candidate sourcing and screening process by automating several parts of the way. However, there are several roadblocks to integrating ATS APIs at scale because of which companies refrain from leveraging the benefits that come along. Try our ROI calculator to see how much building integrations in-house can he.

In the next section we will discuss how to solve the common challenges for SaaS products trying to scale and accelerate their ATS integration strategy.

Addressing challenges of ATS API integration with Unified API

Let's discuss how the roadblocks can be removed with unified ATS API: just one API for all ATS integrations. Learn more about unified APIs here

Challenge 1: Loss of data during data transformation 

When data is being exchanged between different ATS applications and your system, it needs to be normalized and transformed. Since the same details from different applications can have different fields and nuances, chances are if not normalized well, you will end up losing critical data which may not be mapped to specific fields between systems. 

This will hamper centralized data storage, initiate duplication and require manual mapping not to mention screening workflow disruption. At the same time, normalizing each data field from each different API requires developers to understand the nuances of each API. This is a time and resource intensive process and can take months of developer time.

How unified ATS API solves this: One data model to prevent data loss

Unified APIs like Knit help companies normalize different ATS data by mapping different data schemas from different applications into a single, unified data model for all ATS APIs. Data normalization takes place in real time and is almost 10X faster, enabling companies to save tech bandwidth and skip the complex processes that might lead to data loss due to poor mapping.

Bonus: Knit also offers an custom data fields for data that is not included in the unified model, but you may need for your specific use case. It also allows you to to request data directly from the source app via its Passthrough Request feature. Learn more

Challenge 2: Delayed recruitment due to inability of real-time sync and bulk transfers

Second, some ATS API integration has a polling infrastructure which requires recruiters to manually request candidate data from time to time. This lack of automated data updation in real time can lead to delayed sourcing and screening of applicants, delaying the entire recruitment process. This can negatively impact the efficiency that is expected from ATS integration. 

Furthermore, Most ATS platforms receive 1000s of applications in a matter of a few minutes. The data load for transfer can be exceptionally high at times, especially when a new role is posted or there is any update.

As your number of integrated platforms increases, managing such bulk data transfers efficiently as well as eliminating delays becomes a huge challenge for engineering teams with limited bandwidth

How unified ATS API solves this: Sync data in real-time irrespective of data load/ volume

Knit as a unified ATS API ensures that you don’t lose out on even one candidate application or be delayed in receiving them. To achieve this, Knit works on a  webhooks based system with event-based triggers. As soon as an event happens, data syncs automatically via webhooks. 

Read: How webhooks work and how to register one?

Knit manages all the heavy lifting of polling data from ATS apps, dealing with different API calls, rate limits, formats etc. It automatically retrieves new applications from all connected ATS platforms, eliminating the need to make API calls or manual data syncs for candidate sourcing and screening. 

At the same time, Knit comes with retry and resiliency guarantees to ensure that no application is missed irrespective of the data load. Thus, handling data at scale. 

This ensures that recruiters get access to all candidate data in real time to fill positions faster with automated alerts as and when new applications are retrieved for screening. 

Challenge 3: Compliance and candidate privacy concerns

Since the ATS and other connected platforms have access to sensitive data, protecting candidate data from attacks, ensuring constant monitoring and right permission/ access is crucial yet challenging to put in practice.

How unified ATS API solves this: Secure candidate data effectively

Knit unified ATS API enables companies to effectively secure the sensitive candidate data they have access to in multiple ways. 

  • First, all data is doubly encrypted, both at rest and in transit. At the same time, all PII and user credentials are encrypted with an additional layer of application security. 
  • Second, having an events-driven webhooks architecture, Knit is the only unified ATS API which does not store any copy of the customer data in its server. Thus, reducing changes of data misuse further. 
  • Third, Knit is GDPR, SOC II and ISO27001 compliant to make sure all industry security standards are met. So, there’s one less thing for you to worry about.

Challenge 4: Long deployment duration and resource intensive maintenance

Finally, ATS API integration can be a long drawn process. It can take 2 weeks to 3 months and thousands of dollars to build integration with  just a single ATS provider. 

With different end points, data models, nuances, documentation etc. ATS API integration can be a long deployment project, diverting away engineering resources from core functions.

It’s not uncommon for companies to lose valuable deals due to this delay in setting up customer requested ATS integrations. 

Furthermore, the maintenance, documentation, monitoring as well as error handling further drains engineering bandwidth and resources. This can be a major deterrent for smaller companies that need to scale their integration stack to remain competitive.  

How unified ATS API solves this: Instant scalability

A unified ATS API like Knit allows you to connect with 30+ ATS platforms in one go helping you expand your integration stack overnight. 

All you have to do is embed Knit’s UI component into your frontend once. All heavy lifting of auth, endpoints, credential management, verification, token generations, etc. is then taken care of by Knit. 

Other benefits of using a Unified ATS API

Fortunately, companies can easily address the challenges mentioned above and streamline their candidate sourcing and screening process with a unified ATS API. Here are some of the top benefits you get with a unified ATS API:

Effective monitoring and logging for all APIs

Once you have scaled your integrations, it can be difficult to monitor the health of each integration and stay on top of user data and security threats. Unified API like Knit provides a detailed Logs and Issues dashboard i.e. a one page overview of all your integrations, webhooks and API calls. With smart filtering options for Logs and Issues,  Knit helps you get a quick glimpse of the API's status, extract historical data and take necessary action as needed.

API logs and issues

Extensive range of Read and Write APIs

Along with Read APIs, Knit also provides a range of Write APIs for ATS integrations so that you can not only fetch data from the apps, you can also update the changes — updating candidate’s stage, rejecting an application etc. — directly into the ATS application's system. See docs

Save countless developer hours and cost

For an average SaaS company, each new integration takes about 6 weeks to 3 months to build and deploy. For maintenance, it takes minimum of 10 developer hours per week. Thus, building each new integration in-house can cost a SaaS business ~USD 15,000. Imagine doing that for 30+ integrations or 200!

On the other hand, by building and maintaining integrations for you, Knit can bring down your annual cost of integrations by as much as 20X. Calculate ROI yourself

In short, an API aggregator is non negotiable if you want to scale your ATS integration stack without compromising valuable in-house engineering bandwidth.

How to improve your screening workflow with Knit unified ATS API

Get Job details from different job boards

Fetch job IDs from your users Applicant Tracking Systems (ATS) using Knit’s job data models along with other necessary job information such as departments, offices, hiring managers etc.

Get applicant details

Use the job ID to fetch all and individual applicant details associated with the job posting. This would give you information about the candidate such as contact details, experience, links, location, experience, current stage etc. These data fields will help you screen the candidates in one easy step.

Complete screening activities

Next is where you take care of screening activities on your end after getting required candidate and job details. Based on your use case, you parse CVs, conduct background checks and/or administer assessment procedures.

Push back results into the ATS

Once you have your results, you can progmmatically push data back directly within the ATS system of your users using Knit’s write APIs to ensure a centralized, seamless user experience. For example, based on screening results, you can —

  • Update candidate stage using <update stage> API See docs
  • Match scores for CV parsing or add a quick tag to your applicant See docs
  • Reject an application See docs and much more

Thus, Knit ensures that your entire screening process is smooth and requires minimum intervention.

Get started with Unified ATS API

If you are looking to quickly connect with 30+ ATS applications — including Greenhouse, Lever, Jobvite and more — get your Knit API keys today.

You may talk to our one of our experts to help you build a customized solution for your ATS API use case. 

The best part? You can also make a specific ATS integration request. We would be happy to prioritize your request. 

Sudeshna Roy

Head of Content, Knit

Decoding product and generating users with valuable content

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Nov 19, 2023

Whitepaper: The Unified API Approach to Building Product Integrations


We just published our latest whitepaper "The Unified API Approach to Building Product Integrations". This is a one stop guide for every product owner, CTO, product leader or a C-suite executive building a SaaS product.

If you are working on a SaaS tool, you are invariably developing a load of product/customer-facing integrations. After all, that's what the data says.

Not to worry. This guide will help you better plan your integration strategy and also show you how unified APIs can help you launch integrations 10x faster.

In this guide, we deep dive into the following topics:

  • What is a unified API and when to use one
  • The components of unified API
  • The ROI of using a unified API
  • Factors to consider before choosing a unified API provider
  • Comparative analysis of different approaches to building integrations
  • Build vs Buy: What should be your integration strategy?
  • Integration challenges for startups and how to address them

Download your guide here.

Nov 18, 2023

Unified API: All you need to know


Today, SaaS integrations have become a necessity considering the current market landscape ensuring faster time to market, focus on product innovation and customer retention. A standard SaaS tool today has 350+ integrations, where as an early startup has minimum 15 product integrations in place.  

However, building and managing customer facing integrations in-house can be a daunting task, considering they are complicated, expensive and their volume and scope is ever increasing. With rising customer demands for a connected SaaS ecosystem, product owners are always on the lookout for ways to significantly increase their integration shipping time. Therefore, the integration market has seen the steady rise of API aggregators or unified APIs. 

This article will help you understand the diverse aspects of unified API, benefits and how you can choose the right one. 

Here’s what we will discuss here:

  • What is a unified API
  • Rise of unified API
  • Key components of unified API
  • Benefits of unified API
  • ROI of unified APIs
  • How unified APIs ensure a more secure connection
  • When to choose a unified API vs build integrations in-house
  • Workflow automation tools vs unified APIs
  • How to choose the right unified API provider

Let's get started.

What is a unified API?

A unified API is an aggregator or a single API which allows you to connect with APIs of different software by offering a single, standardized interface for different services, applications, or systems. Furthering SaaS integrations, it adds an additional abstraction layer to ensure that all data models and schemas are normalized into one data model of the unified API. 

Rise of unified API

As the volume of integrations have seen an exponential increase, the use of APIs has become more pronounced. With more APIs, complexity and costs of integrations are also increasing. Therefore, the reliance on unified API has seen an increase, guided by the following factors:

Increased API use

  • 90% of the entire developer population across the world uses APIs
  • 69% developers work with third party APIs
  • 98% of large enterprises consider APIs an essential part of their digital transformation strategy
  • 53% enterprises are consuming 3rd party APIs for developing products and services

To know more about API integration, its growth, benefits, key trends and challenges and increased use, check out our complete guide on What is API integration

High cost of in-house integrations

  • Integrations can take anywhere between 2 weeks to 3 months to build, keeping an average of 4 weeks
  • Building integrations require expertise and bandwidth of engineering teams, including QA engineers, product managers and software developers, whose salary can range from USD 80K to USD 125K
  • Therefore, the average cost per integration comes to USD 10K, and companies generally use 100+ integrations, at least 15-20 at a lower spectrum, leading to USD 150K- 200K of integration costs

Building and managing integrations is complex

  • APIs within the same software category can have different schemas and data models, requiring engineering teams to gain knowledge of different rules and architecture
  • Full version APIs might not be freely available for all applications, some might come at an additional cost or premium upgrade
  • Maintaining integrations can be difficult, especially when an API fails, and customer success teams lack the expertise to address these challenges 

Together these factors have been instrumental in the rise of unified API as a popular approach to facilitate seamless integrations for businesses.  

Key components of unified API

Let’s quickly walk through some of the top traits or components which form the building blocks for a good unified API. Essentially, if your unified API has the following, you are in good hands:

Data retrieval and aggregation

As the user requests for data, the Unified API efficiently retrieves relevant information from the concerned APIs. It also aggregates data from multiple APIs, consolidating all required information into a single API call. 

For instance, in a scenario where a user seeks an employee's contact and bank account details, the Unified API fetches and aggregates the necessary data from multiple APIs, ensuring a seamless user experience.


Each application or software that your users want integration with will have distinct data models and nuances. Even for the same field like customer ID, the syntax can vary from cust_ID ro cus.ID and innumerable other options. 

A unified API will normalize and transform this data into a standard format i.e. a common data model and align it with your data fields to ensure that  no data gets lost because it is not mapped correctly. . 

Developers save engineering efforts for mapping, identifying errors in data exchange and understanding different APIs to facilitate normalization and transfer.  

Data sync

Once the data is normalized, the Unified API prepares it for transmission back to the user. This can be executed either via a webhook or by promptly responding to the API request, ensuring swift and efficient data delivery.

Some unified API requires you to maintain a polling infrastructure for periodically pulling data from the source application. While other unified APIs like Knit, follow a push architecture where in case an event occurs, it automatically sends you fresh data to the webhook registered by you.

Benefits of unified API

Now that you understand what constitutes a good unified API, it is important to understand the benefits that unified API will bring along. 

Faster time to market and scalability

Unified API allows engineering teams to go to the market faster with enhanced core product functionalities as time and bandwidth spent on building in-house integrations is eliminated. It enables accelerated addition or deletion of APIs from your product, creating the right market fit. At the same time, you can easily scale the number and volume of integrations for your product to meet customer demands, without worrying about time and cost associated with integrations. 

Reduced costs

As mentioned, building integrations with different APIs for different applications can be highly cost intensive. However, with a unified API, businesses can significantly save on multiple engineering hours billed towards building and maintaining integrations. There is a clear decrease in the hard and soft costs associated with integrations with a potential to save thousands of dollars per integration.  

Reduced maintenance responsibilities

Maintaining several APIs for integrations can be as difficult or at times more difficult than building integrations, as the former is an ongoing activity. A unified API takes out the friction from maintaining integrations and takes care when an API fails, or the application undergoes an upgrade, etc. Also, maintenance responsibilities involve context switching for engineering teams, which leads to a significant wastage of time and efforts. A unified API bears full responsibility for troubleshooting, handling errors and all other maintenance related activities. 

Managing integrations can be time and cost intensive, leading to unnecessary delays, budget challenges and diversion of engineering resources. Our article on Why You Should Use Unified API for Integration Management discusses how a unified API can cut down your integration maintenance time by 85%

Ease of documentation and KT

A unified API ensures that you don’t need to bury yourself in 1000s of pages of documentation for each and every integration or application API. Rather, it allows you to simply gain knowledge about the architecture and rules of the endpoint and authentication for the unified API. Invariably, the documentation is easy to understand and the knowledge transfer is also seamless because it is limited to one architecture. 

Standardized pagination

Pagination, filtering and sorting is an important element when it comes to integration for businesses. All these three elements help applications breakdown data in a way that is easier to consume and use for exchange. A unified API ensures that there is a standardization and uniformity between different formats of pagination, sorting and filtering among applications and it is extremely consistent. This prevents over-fetching or under-fetching of data, leading to more efficient data exchange. 

If you want to learn more about pagination best practices, read our complete guide on API pagination

New revenue opportunities

Finally, a unified API helps you create new revenue or monetization opportunities for businesses by allowing them to offer premium services of connecting all HRIS or CRM platforms on an integrated platform. A unified API has the potential to help customers save time and cost, something they would be willing to pay a little extra for. 

ROI of a unified API

While we have mentioned some of the top benefits of using unified APIs, it is very important to also understand how unified APIs directly impact your bottom line in terms of the return on investment. To enable SaaS companies to decode the business value of unified APIs, we have created an ROI calculator for unified API. Learn how much building integrations in-house is costing you and compare it with the actual business/monetary impact of unified APIs.

Some of the key tangible metrics that translate to ROI of unified APIs include:

I) Saved engineering hours and cost

II) Reduced time to market

III) Improved scalability rate

IV) Higher customer retention rate

V) New monetization opportunities

VI) Big deal closure

VII) Access to missed opportunities

VIII) Better security

IX) CTO sentiment

X) Improved customer digital experiences

To better understand the impact of these metrics and more on your bottom line and how it effectively translates to dollars earned, go to our article on What is the Real ROI of Unified API: Numbers You Need to Know.

Can unified API lead to better security?

A key concern for anyone using APIs or integrations is the security posture. As there is an exchange of data between different applications and systems, it is important that there is no unauthorized access or misuse of data which can lead to financial and reputational damage. Some of the key security threats for API include:

  • Unauthorized access
  • Broken authentication tokens
  • Injection attacks
  • Data exposure
  • Rate limiting and Denial of Service (DoS) attacks 
  • Third party dependencies
  • Human error

Learn more about the most common API security threats and risks you are vulnerable to and the potential consequences if you don’t take action. 

A unified API can help achieve better security outcomes for B2B and B2C companies by facilitating:

1) Authentication and authorization

Unified API adopts robust authentication and authorization models which are pivotal in safeguarding data, preventing unauthorized access, and maintaining the integrity and privacy of the information exchanged between applications. Strong authentication mechanisms, such as API keys or OAuth tokens, are critical to securely confirm identity, reducing the risk of unauthorized access. At the same time role-based access control and granular authorization are integral following the principle of least privilege, giving users the least access which is required to perform their roles successfully. 

Check out this article to learn more about the authentication and authorization models for better unified API security. 

2) Continuous monitoring and logging

A unified API is expected to continuously monitor and log all changes, authentication requests and other activities and receive real time alerts by using advanced firewalls. Some of the best practices for monitoring and logging include using logging libraries or frameworks to record API interactions, including request details, response data, timestamps, and client information, leverage API gateways, to capture data like request/response payloads, error codes, and client IPs, configuring alerts and notifications based on predefined security thresholds. 

Our quick guide API Security 101: Best Practices, How-to Guides, Checklist, FAQs can help you master API Security and learn how unified APIs can further accentuate your security posture. Explore common techniques, best practices to code snippets and a downloadable security checklist.

3) Data classification

A good unified API classifies data to restrict and filter access. Data is often categorized between what is highly restricted, confidential and public to ensure tiered level of access and authentication for better security. 

4) Data encryption

Since data protection is a key element for security with a unified API, there are multiple levels of encryption in place. It involves encryption at rest, encryption in transit and application level encryption as well for restricted data. 

5) Infrastructure protection

Finally, a unified API ensures security by facilitating infrastructure protection. Security practices like network segregation, DDoS protection using load balancers, intrusion detection, together helps ensure high levels of security from a unified API. 

6) API rate limiting & throttling

As mentioned, APIs are prone to DDoS attacks due to high intensity of traffic with an attack intention. Rate limiting and throttling help maintain the availability and performance of API services, protect them against abusive usage, and ensure a fair distribution of resources among clients. 

Go to our article on 10 Best Practices for API Rate Limiting and Throttling to understand how they can advance API security and how a unified API can implement preventive mechanisms in place to handle rate limits for all the supported apps to make their effective use. 

When to choose a unified API?

As a business, you can explore several ways in which you can facilitate integrations rather than building them in-house. However, there are a few instances when you should be using a unified API particularly.

Case I: When you want to integrate applications within the same category

A unified API is one of the best integration solutions if you wish to connect APIs or applications within the same category. For instance, there can be several CRM applications like Salesforce, Zoho, etc. that you might want to integrate, the same goes for HRIS, accounting and other categories. Therefore, a unified API can be a great solution if you have similar category applications to integrate. 

Start syncing data with all apps within a category using a single Knit Unified API. Check out all the integrations available.

Case II: When you have different data models

Secondly, a major use case for unified API comes when you have applications which follow different datasets, models and architecture and you want to standardize and normalize data for exchange. A unified API will add an abstraction layer which will help you normalize data from different applications with diverse syntax into a uniform and standardized format. 

Case III: When you want to ensure data security

Next, when it comes to using a unified API, data security becomes a key benefit. Integrations and data exchange are vulnerable to unauthorized access and ensuring high levels of security is important. With factors like least privilege, encryption, infrastructure security, etc. a unified API is a good pathway to integration when security is a key parameter for you for decision making. 

You can easily check the API security posture of any unified API provider using this in-depth checklist on How to Evaluate API Security of a Third Party API Provider.

Case IV: When you have limited domain expertise

There might be times when your team doesn’t have the domain expertise for a particular application you might be using and may not be well versed with the terminologies there. For instance, if you are using an HRIS application and your team lacks expertise in the HR and payroll space, chances are you won’t be able to understand different data nomenclatures being used. Here, using a unified API makes sense because it ensures accurate data mapping across applications. 

Get Knit Unified API Key

Case V: When you don’t want to spend engineering time in understanding several APIs

Finally, a unified API is the right choice if you don’t want to spend your engineering bandwidth in understanding and learning about different API, their endpoints and architecture. Different APIs are built on REST, SOAP, GraphQL, each of which requires a high level of expertise and understanding, pushing companies to invest in developer hiring with relevant skills and experience. However, when it comes to a unified API, the engineering teams only need to learn about one endpoint and develop knowledge of a single architecture. Usually, unified APIs are built on REST. Thus, you should go for a unified API if you don’t want to invest engineering time in API education. 

If you find yourself conflicted between whether building or buying is the best approach to SaaS integrations and how to choose the right one for you, check out our article on Build vs Buy: The Best Approach to SaaS Integrations to make an informed decision. 

Unified API vs Workflow Automation

While building integrations in-house vs leveraging unified API are two approaches you can follow, there are other paths you can tread under the ‘buying’ integrations landscape. One of the leading approaches is workflow automation. Let’s quickly compare these two approaches under the buying integrations banner.

Workflow automation tools facilitate product integration by automating workflow with specific triggers. These are mostly low code tools which can be connected with specific products by engineering teams for integration with third party software or platforms. Choose workflow automation for:

  • A low code integration solution
  • One-off customer facing integration or integrations for internal use
  • Limited functionalities for data normalization
  • Off-the rack workflows and integration syncs

A unified API normalizes data from different applications within a software category and transfers it to your application in real time. Here, data from all applications from a specific category like CRM, HRMS, Payroll, ATS, etc. is normalized into a common data model which your product understands and can offer to your end customers. Use a unified API for:

  • Standardized customer-facing integrations
  • High levels of data normalization and standardization
  • Scalable integrations that can be replicated across customers
  • A native integration experience which can be scaled efficiently

For a more detailed comparison between these two approaches to make an informed choice about which way to go, check out our article on Unified API vs Workflow Automation: Which One Should You Choose?

How to choose the right unified API?

If you have decided that a unified API is the way to go for you to facilitate better integrations for your business, there are a few factors you must keep in mind while selecting the right unified API among the different options available.

1. Coverage of API endpoints and applications

Start by evaluating how many API endpoints does the unified API cover. As you know that APIs can be built of REST, SOAP, GraphQL, it is important that your unified API covers them all and ensures that you have to learn the rules of a single architecture. At the same time, it is vital that it covers all or at least most of the applications or software that fall under the category you are looking for in a unified API. For instance, there can be thousands of applications within the HRIS category, you must evaluate if the unified API ensures that all HRIS applications or the ones that you use/ might need in the future are covered. 

Taking this example forward, here is a quick comparison between Finch and Knit on which unified HR API is most suited for user data, security and management. 

2. Data storage and security

Second, we mentioned that a good unified API provides you with a strong security posture.Therefore, it is important to check for the encryption and authentication models it uses. Furthermore, security parameters on least privilege, etc. must also be accounted for. A related factor to security is data storage. On the one hand, you must ensure that the unified API is compliant with data protection and other confidentiality laws, since they might have access to your and your customer’s data. On the other hand, it is equally important to ensure that the unified API doesn’t create a copy of customer data which can lead to security risks and additional storage costs. 

3. Pricing structure

Next, you need to check the pricing structure or pricing model being offered by the unified API. Pricing structures can be based on per customer along with platform charges, flat rates for a fixed number of employees and API call based charges. Increasingly, API call based charges are considered to be the most popular among developers as they turn out to be the most cost effective. Other pricing models which are not usage based can be very expensive and not sustainable for many companies. 

4. Data sync model

A unified API can have data sync in different ways, either it is polling first or webhooks first. Gradually, developers are preferring a webhooks first approach where customers don’t have to maintain a polling infrastructure as data updates are dispatched to customers' servers as and when they happen. Depending on your needs, you must evaluate the unified API based on the data sync model that you prefer. 

If you are confused between which unified API provider to choose, here’s a quick comparison of Knit and Merge, two leading names in the ecosystem focusing on data syncs, integration management, security and other aspects to help you choose the platform which is right for you. 

5. Monetization opportunities 

Finally, you should look for unified APIs which can provide you with monetization opportunities in addition to reduced costs and other benefits mentioned above. Gauge and evaluate whether or not the unified API can help you provide additional functionalities or efficiencies to your customers for which you can charge a premium. While it might be applicable for every application category you use, it is always good to have a monetization lens on when you are evaluating which unified API to choose. 

6. Scalability

Make sure your unified API can grow as you add more integrations and data load. Check if it can handle your current and future integrations. Also, ensure it can manage large amounts of data quickly. Use batch processing to handle the incoming data from different sources efficiently.

While these are a few parameters, explore our detailed article on What Should You Look For in A Unified API Platform? while evaluating an API management tool for your business.

7. Integration maintenance

It is important the unified API not only helps you build integrations but also enables you to maintain them with detailed Logs, Issues, Integrated Accounts and Syncs page and supports you to keep track of every API calls, data syncs and requests. 

Learn how Knit can help you maintain the health of your integrations without a headache.

Wrapping up: TL:DR

To conclude, it is evident that unified APIs have the potential to completely reinvent the integration market with their underlying potential to reduce costs while making the entire integration lifecycle seamless for businesses. Here are a few key takeaways that you should keep in mind:

  • A unified API adds an abstraction layer to connect different API for software in the same category
  • The high costs of building and maintaining integrations along with the engineering team drain are the major factors leading to the rise of the unified API
  • It is important to ensure that your unified API normalizes and standardizes data for exchange
  • Security in the form of authentication, encryption, least privilege, data classification, etc. are important parameters that make unified API a preferred choice
  • A unified API is the best option when you wish to integrates similar software category applications and don’t wish to spend engineering bandwidth on learning different architectures
  • Using a unified API can help developers take their products to market faster and scale seamlessly, addressing increasing customer integration needs
  • Factors like data storage, pricing, data sync models, coverage, etc. must be considered while choosing the right unified API for your business

Overall, a unified API can help businesses integrate high volumes of applications in a resource-lite manner, ultimately saving thousands of dollars and engineering bandwidth which can be invested in building and improving core product functionalities for better market penetration and business growth.

If you are looking to build multiple HRIS, ATS, CRM or Accounting integrations faster, talk to our experts to learn how we can help your use case

Nov 18, 2023

API Pagination 101: Best Practices for Efficient Data Retrieval


If you are looking to unlock 40+ HRIS and ATS integrations with a single API key, check out Knit API. If not, keep reading

Note: This is our master guide on API Pagination where we solve common developer queries in detail with common examples and code snippets. Feel free to visit the smaller guides linked later in this article on topics such as page size, error handling, pagination stability, caching strategies and more.

In the modern application development and data integration world, APIs (Application Programming Interfaces) serve as the backbone for connecting various systems and enabling seamless data exchange. 

However, when working with APIs that return large datasets, efficient data retrieval becomes crucial for optimal performance and a smooth user experience. This is where API pagination comes into play.

In this article, we will discuss the best practices for implementing API pagination, ensuring that developers can handle large datasets effectively and deliver data in a manageable and efficient manner. (We have linked bite sized how-to guides on all API pagination FAQs you can think of in this article. Keep reading!)

But before we jump into the best practices, let’s go over what is API pagination and the standard pagination techniques used in the present day.

What is API Pagination

API pagination refers to a technique used in API design and development to retrieve large data sets in a structured and manageable manner. When an API endpoint returns a large amount of data, pagination allows the data to be divided into smaller, more manageable chunks or pages. 

Each page contains a limited number of records or entries. The API consumer or client can then request subsequent pages to retrieve additional data until the entire dataset has been retrieved.
Pagination typically involves the use of parameters, such as offset and limit or cursor-based tokens, to control the size and position of the data subset to be retrieved. 

These parameters determine the starting point and the number of records to include on each page.

Advantages of API Pagination

By implementing API pagination, developers as well as consumers can have the following advantages - 

1. Improved Performance

Retrieving and processing smaller chunks of data reduces the response time and improves the overall efficiency of API calls. It minimizes the load on servers, network bandwidth, and client-side applications.

2. Reduced Resource Usage 

Since pagination retrieves data in smaller subsets, it reduces the amount of memory, processing power, and bandwidth required on both the server and the client side. This efficient resource utilization can lead to cost savings and improved scalability.

3. Enhanced User Experience

Paginated APIs provide a better user experience by delivering data in manageable portions. Users can navigate through the data incrementally, accessing specific pages or requesting more data as needed. This approach enables smoother interactions, faster rendering of results, and easier navigation through large datasets.

4. Efficient Data Transfer

With pagination, only the necessary data is transferred over the network, reducing the amount of data transferred and improving network efficiency.

5. Scalability and Flexibility

Pagination allows APIs to handle large datasets without overwhelming system resources. It provides a scalable solution for working with ever-growing data volumes and enables efficient data retrieval across different use cases and devices.

6. Error Handling

With pagination, error handling becomes more manageable. If an error occurs during data retrieval, only the affected page needs to be reloaded or processed, rather than reloading the entire dataset. This helps isolate and address errors more effectively, ensuring smoother error recovery and system stability.

Common examples of paginated APIs 

Some of the most common, practical examples of API pagination are: 

  • Platforms like Twitter, Facebook, and Instagram often employ paginated APIs to retrieve posts, comments, or user profiles. 
  • Online marketplaces such as Amazon, eBay, and Etsy utilize paginated APIs to retrieve product listings, search results, or user reviews.
  • Banking or payment service providers often provide paginated APIs for retrieving transaction history, account statements, or customer data.
  • Job search platforms like Indeed or LinkedIn Jobs offer paginated APIs for retrieving job listings based on various criteria such as location, industry, or keywords.

API pagination techniques

There are several common API pagination techniques that developers employ to implement efficient data retrieval. Here are a few useful ones you must know:

  1. Offset and limit pagination
  2. Cursor-based pagination
  3. Page-based pagination
  4. Time-based pagination
  5. Keyset pagination

Read: Common API Pagination Techniques to learn more about each technique

Best practices for API pagination

When implementing API pagination in Python, there are several best practices to follow. For example,  

1. Use a common naming convention for pagination parameters

Adopt a consistent naming convention for pagination parameters, such as "offset" and "limit" or "page" and "size." This makes it easier for API consumers to understand and use your pagination system.

2. Always include pagination metadata in API responses

Provide metadata in the API responses to convey additional information about the pagination. 

This can include the total number of records, the current page, the number of pages, and links to the next and previous pages. This metadata helps API consumers navigate through the paginated data more effectively.

For example, here’s how the response of a paginated API should look like -

Copy to clipboard
 "data": [
     "id": 1,
     "title": "Post 1",
     "content": "Lorem ipsum dolor sit amet.",
     "category": "Technology"
     "id": 2,
     "title": "Post 2",
     "content": "Praesent fermentum orci in ipsum.",
     "category": "Sports"
     "id": 3,
     "title": "Post 3",
     "content": "Vestibulum ante ipsum primis in faucibus.",
     "category": "Fashion"
 "pagination": {
   "total_records": 100,
   "current_page": 1,
   "total_pages": 10,
   "next_page": 2,
   "prev_page": null

3. Determine an appropriate page size

Select an optimal page size that balances the amount of data returned per page. 

A smaller page size reduces the response payload and improves performance, while a larger page size reduces the number of requests required.

Determining an appropriate page size for a paginated API involves considering various factors, such as the nature of the data, performance considerations, and user experience. 

Here are some guidelines to help you determine the optimal page size.

Read: How to determine the appropriate page size for a paginated API 

4. Implement sorting and filtering options

Provide sorting and filtering parameters to allow API consumers to specify the order and subset of data they require. This enhances flexibility and enables users to retrieve targeted results efficiently. Here's an example of how you can implement sorting and filtering options in a paginated API using Python:

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# Dummy data
products = [
    {"id": 1, "name": "Product A", "price": 10.0, "category": "Electronics"},
    {"id": 2, "name": "Product B", "price": 20.0, "category": "Clothing"},
    {"id": 3, "name": "Product C", "price": 15.0, "category": "Electronics"},
    {"id": 4, "name": "Product D", "price": 5.0, "category": "Clothing"},
    # Add more products as needed

@app.route('/products', methods=['GET'])
def get_products():
    # Pagination parameters
    page = int(request.args.get('page', 1))
    per_page = int(request.args.get('per_page', 10))

    # Sorting options
    sort_by = request.args.get('sort_by', 'id')
    sort_order = request.args.get('sort_order', 'asc')

    # Filtering options
    category = request.args.get('category')
    min_price = float(request.args.get('min_price', 0))
    max_price = float(request.args.get('max_price', float('inf')))

    # Apply filters
    filtered_products = filter(lambda p: p['price'] >= min_price and p['price'] <= max_price, products)
    if category:
        filtered_products = filter(lambda p: p['category'] == category, filtered_products)

    # Apply sorting
    sorted_products = sorted(filtered_products, key=lambda p: p[sort_by], reverse=sort_order.lower() == 'desc')

    # Paginate the results
    start_index = (page - 1) * per_page
    end_index = start_index + per_page
    paginated_products = sorted_products[start_index:end_index]

    return jsonify(paginated_products)


5. Preserve pagination stability

Ensure that the pagination remains stable and consistent between requests. Newly added or deleted records should not affect the order or positioning of existing records during pagination. This ensures that users can navigate through the data without encountering unexpected changes.

Read: 5 ways to preserve API pagination stability

6. Handle edge cases and error conditions

Account for edge cases such as reaching the end of the dataset, handling invalid or out-of-range page requests, and gracefully handling errors. 

Provide informative error messages and proper HTTP status codes to guide API consumers in handling pagination-related issues.

Read: 7 ways to handle common errors and invalid requests in API pagination

7. Consider caching strategies

Implement caching mechanisms to store paginated data or metadata that does not frequently change. 

Caching can help improve performance by reducing the load on the server and reducing the response time for subsequent requests.

Here are some caching strategies you can consider: 

1. Page level caching

Cache the entire paginated response for each page. This means caching the data along with the pagination metadata. This strategy is suitable when the data is relatively static and doesn't change frequently.

2. Result set caching

Cache the result set of a specific query or combination of query parameters. This is useful when the same query parameters are frequently used, and the result set remains relatively stable for a certain period. You can cache the result set and serve it directly for subsequent requests with the same parameters.

3. Time-based caching

Set an expiration time for the cache based on the expected freshness of the data. For example, cache the paginated response for a certain duration, such as 5 minutes or 1 hour. Subsequent requests within the cache duration can be served directly from the cache without hitting the server.

4. Conditional caching

Use conditional caching mechanisms like HTTP ETag or Last-Modified headers. The server can respond with a 304 Not Modified status if the client's cached version is still valid. This reduces bandwidth consumption and improves response time when the data has not changed.

5. Reverse proxy caching

Implement a reverse proxy server like Nginx or Varnish in front of your API server to handle caching. 

Reverse proxies can cache the API responses and serve them directly without forwarding the request to the backend API server. 

This offloads the caching responsibility from the application server and improves performance.

Simplify API pagination 

In conclusion, implementing effective API pagination is essential for providing efficient and user-friendly access to large datasets. But it isn’t easy, especially when you are dealing with a large number of API integrations.

Using a unified API solution like Knit ensures that your API pagination requirements is handled without you requiring to do anything anything other than embedding Knit’s UI component on your end. 

Once you have integrated with Knit for a specific software category such as HRIS, ATS or CRM, it automatically connects you with all the APIs within that category and ensures that you are ready to sync data with your desired app. 

In this process, Knit also fully takes care of API authorization, authentication, pagination, rate limiting and day-to-day maintenance of the integrations so that you can focus on what’s truly important to you i.e. building your core product.

By incorporating these best practices into the design and implementation of paginated APIs, Knit creates highly performant, scalable, and user-friendly interfaces for accessing large datasets. This further helps you to empower your end users to efficiently navigate and retrieve the data they need, ultimately enhancing the overall API experience.

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