ETL (Extract, Transform, Load) is an essential process for modern data management. With the increasing volume of data that businesses generate, it’s crucial to have efficient and scalable tools to handle the data pipeline.
AWS provides a range of ETL tools, making it easy to extract data from various sources, transform it into a desired format, and load it into data storage systems.
In this article, we’ll explore the top five tools for ETL on AWS data pipelines. These tools are carefully selected based on their capabilities, ease of use, and reliability. Whether you’re just starting with ETL or looking to upgrade your current setup, this article provides a comprehensive guide to help you choose the right tool for your needs.
What is AWS Data Pipeline?
AWS Data Pipeline is a fully managed service by Amazon Web Services (AWS) that helps move data between different AWS services and on-premises data sources.
AWS Data Pipeline sits within the wider AWS ecosystem, making it easy to integrate with other AWS services such as Amazon S3, Amazon Redshift, Amazon DynamoDB, and Amazon EC2. The integration capabilities allow users to create complex data processing workflows using a combination of AWS services, with Data Pipeline acting as the orchestration service to manage the movement of data between services.
What are the key components of AWS Data Pipeline?
The primary components of AWS Data Pipeline are:
- Pipelines define the data movement and processing workflows, which consist of one or more activities executed in a specified order.
- Activities define the individual processing steps executed within a pipeline, such as copying data from one location to another or running a script.
- Preconditions are optional components that determine when an activity should be executed. For example, you can set a precondition to run an activity only if data is present in a specific location, ensuring that data is processed only when available.
In addition to these core components, AWS Data Pipeline includes several features, such as scheduling, error handling, and reporting, that make it easier to manage data pipelines.
Business Use Cases For AWS Data Pipeline
The most popular business case for AWS Data Pipeline is data integration. AWS Data Pipeline simplifies the process of unifying data from different sources into a data warehouse or a data lake, making it easier for businesses to analyse and make decisions based on that data. This includes integrating data from databases, applications, files, cloud services, and more.
Continuous data migration is yet another key use case for AWS Data Pipeline. Moving data from on-premises sources to cloud services like Amazon S3 or Redshift can be challenging, but AWS Data Pipeline provides a reliable and scalable solution for this process. With Data Pipeline, businesses can take advantage of the benefits of cloud computing while minimizing the risks associated with data migration.
What are the key features of AWS Data Pipeline?
Here are some of the key features of the AWS Data Pipeline.
- Automates workflows between sources and targets, including AWS and on-premise sources like JDBC-based databases
- Supports scheduling and task chaining based on task success or failure.
- Offers comprehensive transformations with activities like HiveActivity, PigActivity, SQLActivity, and custom code-based transformations through HadoopActivity.
- Allows customers to use on-premise systems for data sources or transformations, with task runners on those systems.
- It provides cost-effective pricing as businesses only pay for used compute resources and a flat fee for periodic tasks.
- It has a simple interface that enables customers to set up complex workflows with ease.
Top 7 Tools for ETL on AWS Data Pipeline
1. Equalum
Equalum is an end-to-end ETL platform that provides real-time data integration and transformation capabilities on top of AWS Data Pipelines. It has built-in connectors to AWS services (including S3, RDS, and EMR) for a quick and seamless setup.
Key features:
- CDC capabilities: Streams real-time data into AWS services via industry-leading CDC capabilities.
- Extensive connectivity options: Supports a wide range of data sources and targets, and seamless connections between AWS services, other cloud services and legacy systems/on-premise sources.
- Reduce labor costs: Supports data replication of thousands of objects automatically and supports changes with end-to-end schema evolution, so your data engineers don’t need to spend time on this.
Best for: Cost reduction. Equalum replicates your operational and transactional data into AWS services. It automates time-consuming administration tasks like error handling, data consistency, and monitoring, so you can leave Equalum to integrate the pipelines without worrying about incorrect, missing, or duplicate data.
Review: “Equalum provides a single platform for core architectural use cases, including CDC replication, streaming ETL, and batch ETL. That is important to our clients because there is no other single-focus product that covers these areas in that much detail, and with this many features on the platform.”
2. AWS Glue
AWS Glue is one of the most popular AWS ETL tools. It is a fully managed ETL service that simplifies data movement and transformations on AWS Data Pipelines. It offers seamless integration with other AWS services, making it a popular choice among data engineers.
Key features:
- Serverless infrastructure: Runs ETL jobs without needing to manage any servers.
- Dynamic data discovery: Automatically discovers data and schemas in AWS data stores.
- Automated code generation: Generates PySpark or Scala code for transformations and data cleaning.
Best for: Companies looking for a fully managed solution that integrates seamlessly with other AWS services and can scale with changing data demands. With its serverless infrastructure and automated code generation, it reduces the operational overhead associated with data pipelines.
Review: “We utilize AWS Glue in all of our data pipelines and use it to sync external and internal data sources and auto-generate SQL-based ETL based on AWS Glue catalog objects.”
3. AWS Kinesis
AWS Kinesis is a real-time data streaming service provided by AWS. It helps organizations process and analyze large data streams in real-time, making it ideal for big data processing.
Key features:
- Real-time streaming: Processes data as it arrives, which is especially important for time-sensitive applications.
- Scalable: Handles large volumes of data, and you can easily scale the number of shards based on your needs.
- Secure: Secures the data in transit and at rest.
Best for: Real-time data processing and analysis, as well as for event-driven applications that require low-latency data processing.
Review: “We used kinesis mainly for batch-processing events in a microservices architecture. The best thing about kinesis would be easy integration and compatibility with other AWS products.”
4. Hevo Data
Hevo Data offers real-time data migration with a completely automated setup. With integrations with sources and targets like S3 buckets, SaaS apps, and Amazon Redshift, getting set up and implementing ETL without coding expertise is possible.
Key features:
- Automated data migration: Hevo provides automated data migration from various data sources, including databases and cloud storage, to AWS Data Pipeline.
- Real-time data transfer: Hevo offers real-time data transfer from the data source to AWS Data Pipeline with minimal latency.
Best for: Organizations looking for a simple, easy-to-set-up solution for data integration that doesn’t require expert knowledge.
Review: “It really helped us out of a jam in figuring out our data warehouse strategy and implementation.”
5. Talend
Talend is an open-source data integration tool that enables organizations to efficiently manage large-scale data transfers and transformations. It supports a wide range of data sources and destinations, including AWS data pipelines, making it a popular choice for ETL on the cloud.
Key features:
- Integration options: Supports integration with AWS data pipeline and other cloud platforms
- Easy to set up: Offers a comprehensive library of pre-built connectors and data transformations
- Deployment options: Supports deployment on-premise, in the cloud, or as a hybrid solution.
Best for: Organizations looking for an open-source ETL solution that can handle large-scale data transfers and transformations with ease.
Review: “It enables users to scale up and down services as needed. In addition, backup and catastrophe recovery are automated; that’s an advantage.”
6. Keboola
Keboola’s platform has 400 pre-built connectors to help you get started with ETL (and “reverse ETL,” as seen in the image above, which is another ETL use case) quickly, so you can deliver data to all users across your company. It’s an AWS Partner and offers integration with S3.
Key features:
- Extensive documentation: Engineers who need support can find plenty of it in Keboola’s widely available documentation.
- Customer service: Keboola has a team of over 100 data partners to help with integration and setup.
Best for: An online support network and community. As well as Keboola documentation, you’ll find forums and informative articles.
Review: “The good collection of extractors & writers, simplicity in building direct ETLs, and ease of setup the orchestrations.”
7. StreamSets
You can execute the StreamSets data integration platform on a range of data processing platforms on AWS, including EC2 and Elastic. It’s an AWS Data & Analytics Competency holder and Advanced Technology Partner.
Key features:
- Data drift detection: StreamSets helps identify when there’s a problem with your pipelines with the data drift detection feature.
- Native integration: It integrates with AWS Linux 2, Redshift, Kinesis, S3, and more.
Best for: StreamSets supports both streaming and batch pipelines.
Review: “Build fast and efficient data pipelines. Setting up environments is not complex and can be done within minutes.”
Unlock the Power of AWS Data Pipeline with Equalum
There are several powerful tools available for performing ETL on AWS Data Pipelines, each with its own strengths and capabilities. If you are looking to take advantage of the power of the AWS ecosystem, Equalum stands out as a comprehensive solution that offers native integration with AWS services and a user-friendly platform for advanced data transformations and automated data replication.
We invite you to discover the full potential of real-time data analytics with Equalum. Get started today.
