Today most organizations are of the opinion that public APIs should be tapped into and useful information extracted there from. The same, however triggers a sound ETL solution to handle the data correctly. This blog REST API ETL Tools will talk about the various tools that will help you fetch data from Public APIs and will give you detailed steps on how to use Hevo in-order to fetch data from Public APIs.
What is ETL?
ETL, or Extract, Transform, Load, is a crucial process in data integration that involves three key steps:
- Extracting data from various sources, such as databases and APIs.
- Transforming the data into a suitable format, ensuring data quality and consistency.
- Loading the transformed data into a data warehouse or storage system for analysis and reporting.
Looking for the best ETL tools to connect your data sources? Rest assured, Hevo’s no-code platform helps streamline your ETL process. Try Hevo and equip your team to:
- Integrate data from 150+ sources(60+ free sources).
- Utilize drag-and-drop and custom Python script features to transform your data.
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What are API ETL Tools?
API ETL tools help extract data from different APIs, transform it, and load the information into a central data repository. The use of API ETL tools helps organizations in simplifying the integration process by accumulating data from multiple sources.
- Data Integration: Seamlessly connect and integrate data from multiple APIs, enabling centralized data management.
- Automation: Automate the ETL processes, reducing manual work and the likelihood of errors.
- User-Friendly Interface: Intuitive no-code interfaces allow non-technical users to configure and manage data workflows easily.
What are REST API ETL Tools?
- ETL tools for REST API focus only on integrating data from RESTful APIs, which enables organizations to tap into live data from web services. These also present a structural method of managing and transforming the data in keeping with requirements of the business.
- It offers real-time access to live data from RESTful web services. This, in turn, provides timely updates of data in the corresponding repositories.
- Standardized Data Handling: Utilize standard HTTP verbs- GET, POST, PUT, DELETE-for uniform data manipulation, which makes it easier to integrate with other systems.
- The data transformation functionalities include integrated tools for cleansing and enriching the data. This would ensure proper quality of data at the time of loading into target systems.
Why should you migrate from Public API’s to Data Warehouse?
- Data migration to a data warehouse will allow organizations to bring information from multiple APIs into one single source, which will help make such information much more accessible and easier to analyze.
- Enhanced Data Analysis: A data warehouse supports advanced analytics, which helps businesses to gain actionable insights from large datasets efficiently.
- Data Quality and Consistency: ETL helps in maintaining quality and consistency of data, and it makes the process of keeping proper and accurate records and reports relatively easy.
Load Data from Amazon S3 to Snowflake
Load Data from AWS Elasticsearch to Redshift
Load Data from MySQL to BigQuery
Top Public APIs ETL Tools
1. Hevo
Rating: 4.3(G2)
Hevo is a no-code data pipeline platform that simplifies data integration from public APIs to data warehouses. With its easy-to-use interface, users can effortlessly connect to REST APIs as a data source and automate data ingestion processes.
What makes Hevo unique?
- No-Code Platform: Hevo requires no coding knowledge, making it accessible for users at all technical levels.
- Real-Time Data Replication: Hevo enables real-time data updates, ensuring that your data warehouse is always current.
- Built-in Data Transformation: Hevo provides data transformation capabilities, allowing users to clean and enrich data during the ETL process.
2. Airbyte
Rating: 4.5(G2)
Airbyte is an open-source data integration tool designed to sync data from various sources, including public APIs, to data warehouses. It offers a wide range of connectors and allows users to create custom connectors easily.
Pros and Cons:
Pros | Cons |
Strong community support | Can require technical expertise for setup |
Open-source and customizable | Limited out-of-the-box connectors |
3. Fivetran
Rating: 4.2(G2)
Fivetran is a data integration tool that automates data extraction, transformation, and loading from various sources, including public APIs. It provides a set of pre-built connectors that simplify the ETL process.
Pros and Cons:
Pros | Cons |
Quick setup with pre-built connectors | Pricing can be high for large data volumes |
Automated schema migrations | Limited customization options |
Load Data from Amazon S3 to Snowflake
Load Data from AWS Elasticsearch to Redshift
Load Data from MySQL to BigQuery
4. Stitch Data
Rating: 4.4(G2)
Stitch Data is a cloud-based ETL service that allows users to replicate data from multiple sources, including public APIs, to data warehouses. It is known for its ease of use and robust data integration capabilities.
Pros and Cons:
Pros | Cons |
User-friendly interface | Limited transformation features |
Supports a variety of sources | Pricing can be high for larger datasets |
5. Matillion
Rating: 4.4(G2)
Matillion is a cloud-native ETL tool that enables users to integrate data from public APIs into cloud data warehouses. It offers a rich set of features for data transformation and orchestration.
Pros and Cons:
Pros | Cons |
Easy integration with cloud platforms | Requires some technical knowledge |
Robust transformation capabilities | Higher cost for small businesses |
6. Airflow
Rating: 4.3(G2)
Apache Airflow is an open-source platform designed for programmatically authoring, scheduling, and monitoring workflows. While it is not a dedicated ETL tool, it can orchestrate ETL tasks and connect to various public APIs.
Pros and Cons:
Pros | Cons |
Highly customizable workflows | There is a Steep learning curve for beginners |
Strong community and support | Requires technical setup |
7. Talend
Rating: 4.0(G2)
Talend now acquired by Qlik is an ETL tool that provides a comprehensive suite of data integration and transformation capabilities. It supports connecting to various public APIs for data ingestion.
Pros and Cons:
Pros | Cons |
Active community and support | Can be complex to set up |
Extensive data transformation tools | Requires a license for advanced features |
8. Pentaho Data Integration
Rating: 4.3(G2)
Pentaho is a powerful data integration and analytics platform that offers ETL capabilities for connecting to public APIs. It allows users to create and manage complex data workflows efficiently.
Pros and Cons:
Pros | Cons |
Good reporting and analytics capabilities | May require technical expertise for advanced use |
Robust data integration features | UI can be less intuitive |
9. Microsoft SSIS
Rating: 4.3(G2)
SQL Server Integration Services (SSIS) is a data integration tool from Microsoft that allows users to create data-driven workflows for data extraction, transformation, and loading. It can connect to various public APIs.
Pros and Cons:
Pros | Cons |
Powerful data transformation capabilities | Steeper learning curve for new users |
Deep integration with Microsoft products | Requires SQL Server license |
10. Rivery
Rating: 4.7(G2)
Rivery is a cloud-based ETL platform designed for data integration and management. It enables users to connect to public APIs and automate data workflows efficiently.
Pros and Cons:
Pros | Cons |
Supports a wide range of data sources | Pricing can be high for small businesses |
User-friendly interface | Limited customization options |
Factors to consider when selecting the right ETL solution for your Public API’s:
- Compatibility: Ensure the ETL tool can seamlessly connect to the public APIs you are using.
- Scalability: The solution should be able to handle increasing data volumes as your business grows.
- User-Friendliness: A user-friendly interface can simplify the data migration process, reducing the learning curve for your team.
Step by Step Guide to Pull Data from Public APIs within Minutes:
Prerequisites:
- Access to Hevo’s product. You can go to Hevo and create a new account for Free.
- API url that you want to access.
Step 1: Setup your Public API as a source
Step 1. a) Create a new Pipeline
Step 1. b) From the list of sources search for REST API and configure your REST API source by filling in the required credentials.
Note: If you want to access a public API you can keep Authentication as No Auth
Step 2: Configure your Destination
Step 2. a) Next step is to configure your destination.
Note: For this guide I’ll pick my destination as Snowflake you can pick any destination from the vast number of options that Hevo provides.
Step 2. b) Search for Snowflake in the destinations window, and fill in the required credentials.
With these two simple and easy steps, you have successfully connected your public API to your destination.
Conclusion
Moving data from public APIs to the data warehouse is important data management and analysis. Advanced ETL tools, such as Hevo, Airbyte, and Fivetran, can help organizations streamline their data integration processes and ensure access to the most updated information. When selecting an appropriate ETL solution, compatibility, scalability, and user-friendliness become a matter of consideration, and in return, you are optimizing the entire data strategy to drive valuable insights. Then, investment in the appropriate tools will enable businesses to extract more value from their data assets while the data landscape continues to evolve.
FAQ on Best API ETL Tools
1. What is ETL in API?
ETL in API stands for extracting data from different APIs and then transforming the same into a suitable format so that it can be loaded into a target system like data warehouse, thereby enabling effective consolidation and analysis of data from multiple sources.
2. What are the 4 types of ETL tools?
a. On-Premises ETL Tools
b. Cloud-Based ETL Tools
c. Open-Source ETL Tools
d. Real-Time ETL Tools
3. What is the difference between API and ETL tools?
APIs are interfaces that allow the communication between different software systems and facilitate exchanges of data, while ETL tools extract data from different sources, transform them, and load them into a centralized repository where the data is analyzed.
Kamlesh Chippa is a Full Stack Developer at Hevo Data with over 2 years of experience in the tech industry. With a strong foundation in Data Science, Machine Learning, and Deep Learning, Kamlesh brings a unique blend of analytical and development skills to the table. He is proficient in mobile app development, with a design expertise in Flutter and Adobe XD. Kamlesh is also well-versed in programming languages like Dart, C/C++, and Python.