Businesses like yours need to connect applications and data sources to better serve customers, automate processes, and improve decision-making.
Four things you should know about this topic:
- API integration and data integration are two methodologies that can improve business processes in your organization.
- API integration involves connecting two or more APIs to improve data sharing between applications.
- Data integration is a broad term that means connecting data between two or more data sources.
- Data integration techniques include ETL, ELT, Reverse ETL, and CDC.
In this guide, learn the differences between API integration and data integration to decide which method is best for your data needs.
Table of Contents
What Is an API?
Before you learn about API integration, here's a quick recap of APIs:
An API allows two or more applications to communicate with one another via different protocols and definitions. "Applications" in this context refers to web-based applications accessed through the Hypertext Transfer Protocol (HTTP).
What does API stand for? Application programming interface.
Amazon has a great example of an API in action:
"The weather bureau's software system contains daily weather data. The weather app on your phone 'talks' to this system via APIs and shows you daily weather updates on your phone."
APIs allow information to flow between applications seamlessly. Using the above example, the weather app on your phone connects to the internet and delivers data to a server. The server interprets the data and changes it to a more readable format before sending it back to your phone. Without an API, your weather app wouldn't work correctly.
There are four main types of API:
- Public APIs (Most of these APIs are RESTful APIs/REST APIs)
- Partner APIs
- Private APIs
- Composite APIs
Each one has a different scope of use and level of access. However, all these APIs essentially do the same thing: They connect applications in one way or another.
Recommended reading: Types of APIs & Popular REST API Protocol
What Is API Integration?
API integration happens when two or more applications connect through their respective APIs. The purpose of API integration is to keep data in sync and optimize the sharing of data between applications. That can improve multiple business processes and provide your organization with more value.
API integration involves knowledge of application logic. Typically, data engineers will use the programming language JSON to exchange data between two APIs. Engineers will refer to API documentation during integration and make requests to URLs with parameters. Those parameters might include an access key or API token. Without API integration tools, this process can be extremely time-consuming.
Here are a few API integration examples in the business world:
- An organization has a web-based customer relationship management (CRM) system and an enterprise resource planning (ERP) system and wants to compare data in both tools. An API integration platform will connect the CRM API with the ERP API so the systems can exchange data.
- One of the most common uses of APIs is data aggregation. Credit card comparison websites collect information from multiple third-party lenders and display interest rates and other data in real-time. That allows consumers to check the credit cards with the best rates and conditions before applying for finance. API integration facilitates this entire process.
- Social media platforms use API integration to fetch data from news sources and display this information on news feeds.
It's important to note here that not every application has an API. Businesses might need to hire a developer to create an API for a particular objective, such as connecting data between two legacy systems.
As previously mentioned, most public APIs are now REST APIs. The majority of API integration projects involve REST APIs in some way because they are easy to integrate and scale. That allows for a seamless flow of information between two or more data sources.
Integrate.io's REST API connector helps with API integration by offering complete authorizations, response parsing, JSON path expression, rate limiting, and other benefits. You can use the connector to connect to a REST API and extract the data needed for your pipeline.
Recommended reading: What is API Management?
Benefits of API Integration
Here are some of the benefits of API integration for your business:
Automate Day-to-Day Tasks
API integrations remove manual data entry when exchanging information between two or more data sources. You can save time, reduce labor costs, and decrease human error.
Improve Business Processes
API integrations allow you to connect different applications in your business for better usability, functionality, operational performance, problem-solving, and decision-making. For example, you can integrate two APIs to view information about sales processes in your company and generate more revenue.
Make Applications More Effective
By integrating one application with another, you can make each application more effective for your business needs. For instance, integrating the API of a database with that of an analytical tool will allow you to view metrics and key performance indicators within the database rather than switching between systems.
Improve Services for Application End Users
API integration can result in better-performing applications. For example, you can integrate a self-service business application with a password management application so end users don't have to keep entering their sign-on details every time.
What Is Integration?
It's important to define integration. Data integration is a broad term that essentially means connecting data from different sources for a particular objective. Integrating data can include various processes and professionals, such as data engineers.
Typically, data integration involves engineers creating big data pipelines that move data from one location to a supported target system. However, a data integration platform like Integrate.io can simplify this process by reducing the amount of code usually required for pipeline-building. No-code/low-code connectors can move data between locations seamlessly without any of the hard work normally associated with integration.
More companies like yours are investing in data integration to consolidate data from separate sources. Experts believe the global data integration market will reach $19.09 billion in 2026 at a compound annual growth rate of 11.99%.
Different Data Integration Types
There are various data integration processes and methodologies. Here are the most effective and popular:
ETL stands for Extract, Transfer, Load. It is one of the fastest and most reliable data integration methods: ETL involves:
- Extracting data from a source and placing it into a staging area. That source might be a relational database, CRM, ERP, SaaS tool, or social media platform.
- Transforming the data into a suitable and workable format for a target system such as a data warehouse or data lake. Engineers might cleanse the data and make sure it complies with data governance frameworks like GDPR. The transformation stage might also involve removing data duplicates and improving data quality.
- Loading the data into the target system.
At this point, you can run data through business intelligence (BI) tools such as Looker and Tableau and identify trends and patterns in data sets.
ELT stands for Extract, Load, Transfer. It's a similar data integration process to ETL but reverses the "transfer" and "load" stages of the process. ELT involves:
- Extracting data from a data source like a relational database or CRM.
- Loading the data into a target system like a data warehouse immediately.
- Transforming the data into a suitable and workable format in the target system.
Deciding between ETL and ELT might depend on the data in your organization. ETL is best for smaller data sets that need complicated transformations. ELT is more suitable for larger data sets that contain structured and unstructured data.
Reverse ETL lets you move data from a target system, such as a warehouse, into an operational system like a CRM or ERP. That lets you view data analytics and other information inside the software tools your team knows how to use. For example, you can move data from Amazon Redshift (a data warehouse) to Salesforce (a CRM system).
CDC stands for Change Data Capture. It's a data integration process that monitors changes made to data sets in a database. You can access real-time (or near-real-time) data movement and process data as database events happen. CDC can provide low latency and scalable data replication.
Many data integration platforms only enable one or two of the above methods, which might hinder your business objectives. Integrate.io lets you move data to your desired location via ETL, ELT, Reverse ETL, or super-fast CDC.
Benefits of Data Integration
Here are some of the benefits of data integration:
Some of the systems in your organization might have security vulnerabilities. For example, your team might use a legacy database that no longer receives updates and security patches from its vendor. In scenarios like this, you can move data from insecure systems to a target system like a warehouse for improved security. The best data warehouses protect your data and prevent data breaches.
Single Source of Truth
Moving data sets to a centralized target system provides you with a single source of truth for that data. You can view data sets in one place rather than switching between multiple systems for data management. For example, moving customer-related data from different databases and CRMs to a data warehouse gives you a 360-degree view of your customers.
Moving data to a data warehouse and then running that data through BI tools lets you generate intelligence about your business processes. You can identify patterns in data and make better decisions that benefit your company. For example, you can move inventory data to a warehouse, push that data through a BI tool, and learn which inventory processes provide the greatest return on investment.
Remove Data Silos
Many systems are unable to communicate with one another, causing data silos between different departments in an organization. By moving data from disparate sources to a centralized location, you can remove these silos and get a holistic view of how your company is performing. You can view data sets in one single system and improve data management.
Data governance frameworks like GDPR, CCPA, and HIPAA set strict guidelines for collecting, processing, and storing data. Legacy systems might have security vulnerabilities that increase the risk of data breaches, resulting in violations of these frameworks. Moving data to a centralized target system like a data warehouse can improve data security and prevent expensive fines for non-compliance with data legislation.
Recommended reading: 17 Best Data Integration Platforms
API vs. Integration: Which Method Should You Choose?
API integration and data integration serve different purposes:
- Integrating APIs involves connecting two or more applications through their APIs to exchange data. Data integration typically involves connecting data from different sources and moving that data to a target system.
- Integrating APIs can sync data between two or more applications and make those applications more effective. Data integration usually connects data for the purpose of data analysis (running data through BI tools after moving it to a warehouse, for example.)
- Integrating APIs usually involves coding JSON to exchange data between APIs. Data integration involves the building of big data pipelines to move data from one location to another.
Choosing between API integration and data integration depends on your use case. Here are two scenarios to consider when weighing these methods:
- You want to fetch data from Shopify and Mailchimp. You can bring data from those sources into your pipeline with a REST API connector, extracting data from Shopify and Mailchimp APIs without custom development. Moving data via a REST API connector is a relatively simple task. However, most businesses will struggle to write data to an API because it requires extensive data engineering skills.
- You have a web-based relational database and CRM system in your organization. You want to compare data in both systems for better decision-making. A data integration method like ETL can help you achieve this goal. You can extract data from the relational database and CRM, transform those datasets into the correct format for analytics, and move data to a data warehouse. Then you can run newly transformed data through a BI tool.
Recommended reading: Top 14 ETL Tools for 2023
How Integrate.io Helps With API and Data Integration
Whether you decide to integrate APIs or data in your organization, Integrate.io can help in the following ways:
- Integrate.io's API lets you control and monitor Integrate.io clusters and jobs. You can use this API when working in the Integrate.io platform to create clusters, run jobs, track those jobs, and quit jobs and clusters currently running.
- Integrate.io's REST API connector lets you extract data from sources into your pipeline without advanced skills.
Integrate.io's suite of data integration tools lets you move data between locations without the hard work. For example, you can perform ETL and ELT processes with no-code/low-code connectors and reduce the amount of coding and data engineering associated with pipeline building. Alternatively, use Reverse ETL to move data from a target location to an operational system or track database changes in real time or near real time with super-fast CDC.
Integrate.io makes API and data integration simple. The platform removes the pain points and jargon commonly associated with these processes, providing all the tools for your data needs.
Other benefits of using Integrate.io include:
- Exceptional customer service
- Simple workflow creation
- Enhanced data security
- Compliance with data governance frameworks when managing data
- Salesforce-to-Salesforce data integrations
Integrate.io can help you achieve your API and data integration objectives. This platform lets you move RESTful data to a target system or transfer data from sources to a destination seamlessly with its native out-of-the-box connectors. Schedule an intro call now!