Top 8 AWS ETL Tools to Consider in 2024

The ETL process extracts information from sources such as Databases, converts files or tables according to Data Warehouse standards, and loads them into the data warehouse.

Are you confused about which tool to use for ETL from your AWS account? Don’t worry this blog will discuss the Amazon ETL process in detail and also tell you about some of the best AWS ETL tools that make the entire process easy and efficient.

What is AWS ETL?

• AWS provides a Glue for performing extract, transform, and load (ETL). The product consists of a serverless platform and necessary tools for carrying out data integration. It also helps to modify your data based on your use case.

Top 8 AWS ETL Tools to Consider in 2024

1. Hevo Data

• Hevo allows you to replicate data in near real-time from 150+ sources to the destination of your choice including Snowflake, BigQuery, Redshift, Databricks, and Firebolt.
• Hevo is the only real-time ELT No-code Data Pipeline platform that cost-effectively automates data pipelines that are flexible to your needs. For the rare times things do go wrong, Hevo ensures zero data loss.
• To find the root cause of an issue, Hevo also lets you monitor your workflow so that you can address the issue before it derails the entire workflow.
• Add 24*7 customer support to the list, and you get a reliable tool that puts you at the wheel with greater visibility. Check Hevo’s in-depth documentation to learn more. Hevo offers a simple and transparent pricing model.

Hevo was the most mature Extract and Load solution available, along with Fivetran and Stitch but it had better customer service and attractive pricing. Switching to a Modern Data Stack with Hevo as our go-to pipeline solution has allowed us to boost team collaboration and improve data reliability, and with that, the trust of our stakeholders on the data we serve.

– Juan Ramos, Analytics Engineer, Ebury

Pro Tip:- Imagine never having to maintain ELT Modern data teams across the world automate data integration from 150+ sources using Hevo Pipeline because it is reliable, intuitive and requires virtually zero maintenance.

2. AWS Glue

• AWS Glue is one of the most popular ETL Tools in AWS in the current market. It is a completely managed ETL platform that simplifies the process of preparing your data for analysis.
• It is very easy to use, all you have to do is create and run an ETL job with just a few clicks in the AWS Management Console. You just have to configure AWS Glue to point to your data stored in AWS.
• It automatically discovers your data and stores the related metadata in the AWS Glue Data Catalog. Once this is done, your data can be searched and queried immediately and is also available for ETL.

Use Case

• AWS Glue is to be used when your use case is primarily ETL and when you want your jobs to run on a serverless Apache Spark-based platform. It can also be used when your data is semi-structured or has an evolving schema. 

Pricing

• You pay hourly when you use AWS Glue, billed by the second, for crawlers and ETL jobs. For this Amazon ETL Tool, you only have to pay a simple monthly fee, according to the AWS Glue Data Catalog. Also, the first million objects and accesses are stored for free.

3. AWS Data Pipeline

• AWS Data Pipeline is among the most reliable AWS ETL Tools. It helps to move data between different AWS compute and storage services and on-premises data sources at specified intervals.
• It allows you to access your data where it’s stored regularly, transform and process it as needed, and efficiently transfer the resultant data to AWS services such as Amazon RDS, Amazon S3, Amazon DynamoDB, and Amazon EMR.
• AWS Data Pipeline is fault-tolerant, repeatable, and highly available and lets you easily develop complex data processing workloads. AWS Data Pipeline eliminates the need to take care of resource availability, management of inter-task dependencies, resolve transient failures or timeouts in individual tasks, or even develop a failure notification system.
• This Amazon ETL Tool helps you claim and process data that was previously locked up in on-premises data silos.

Use Case

• Using AWS Data Pipeline is best suited for daily data operations as it does not require maintenance effort. It also allows you to run and monitor your processing activities on a highly reliable, fault-tolerant infrastructure.
• It is suitable for copying data between Amazon Amazon S3 and Amazon RDS or running a query against Amazon S3 log data.

Pricing

• As part of AWS’s Free Usage Tier, you can get started with AWS Data Pipeline for free. For further pricing information, check out this page.

4. Stitch Data

• Stitch provides support for Amazon Redshift and S3 destinations. It also integrates with over 90 data sources.
• It maintains SOC 2, HIPAA, and GDPR compliance while providing businesses the power to replicate data easily and cost-effectively. Stitch, being a Cloud-first, extensible platform, lets you scale your ecosystem reliably and integrate with new data sources 

Use Case

• Stitch Data is recommended when you want better insight into data analytics. It lets you move your AWS data to your data warehouse within minutes.
• It does not require API maintenance, scripting, cron jobs, or JSON and is very easy to use. It can be used by someone without a technical background. It allows quick connections to first-party data sources, including MySQL, MongoDB, Salesforce, and Zendesk.

Pricing

• You can see the entire pricing plan of this Amazon ETL Tool here.

5. Talend

• AWS integration strategies may be daunting for many, but it doesn’t have to be. It is important to choose the right integration tool, to simplify the entire process and carry it out quickly and reliably.
• Talend Cloud Integration Platform supports different types of integrations, including on-premise, cloud, and hybrid, with AWS. You will find graphical tools, an integration template, and more than 900 components at your disposal to ensure your integration is successful.

Use Case

• Talend is suitable for data preparation, data quality, data integration, application integration, data management, and big data among other things. Talend provides separate products for each solution.

Pricing

• Talend provides a free trial. You can view the entire pricing plan here.

6. AWS Kinesis

• Amazon Kinesis Data Streams is one of the important AWS Redshift Amazon ETL tools. It enables you to analyze huge amounts of data in real time.
• You have to add data to your Redshift cluster using AWS Kinesis. After reading a stream of events from Kinesis, it applies processing or transformations to these data. Then, in Amazon SCTS,  it writes the results into a destination table. This makes Amazon Kinesis one of the popular AWS data transformation tools.

Use Cases

• You can create real-time data solutions and feed live data into your data warehouse using Kinesis Streams. It can be used in IOT sensors, financial markets, and websites for data analysis. 

Pricing

• AWS Kinesis offers short-term free trials and further pricing can be checked here.

Other AWS ETL Tools are available such as:

• Amazon EMR (Elastic MapReduce)
• AWS Step Functions
• Amazon Redshift
• Amazon Athena
• AWS DMS (Database Migration Service)
• Amazon Managed Workflows for Apache Airflow (MWAA)
• AWS Glue DataBrew

7.  Informatica    

• Regarded as one of the best ETL tools for AWS, Informatica offers built-in features that allow it to easily connect with various source systems.
• It offers a versatile graphical user interface that can design ETL processes, debug, and monitor sessions.

Use Cases

• It can be used in healthcare, pharma, finances, and fraud detection for real-time data analysis. It is also used in data warehousing, business intelligence, and data integration among business applications.

Pricing

• Informatica offers a free trial, and a detailed pricing plan is available here

8. Integrate.io

• Integrate.io is a cloud-based data integration platform offering ETL (Extract, Transform, Load) capabilities.
• It enables you to connect to various data sources, transform data through code or pre-built functions, and load it into target destinations.
• Its features such as extensive connectivity, visual interface, and security make it one of the most sought-after AWS ETL tools. 

Use Cases

• Integrate.io is a suitable ETL tool for use in finance, banking, and e-commerce for data warehousing, real-time data processing, and automation. 

Pricing

• Integrate.io offers a free trial and you can check out its detailed pricing plans here

Comparing the 5 Best ETL Tools

Use Cases of AWS ETL Tools

1) Build Event-driven ETL Pipelines

• AWS Glue enables you to prevent any processing delays. It allows you to start your ETL tasks as soon as any new data arrives.
• So, while you will load new data in your Amazon S3 account, the ETL process will start working in the background.

2) Create a Unified Catalog

• The AWS Glue provides a Data Catalog using which you can discover multiple AWS datasets quickly without even shifting any data. Furthermore,
• Once you successfully catalog the data, you can access it for searching and querying using Amazon Athena, Redshift Spectrum, etc.

3) Create and Monitor ETL Jobs Without Coding

• You can seamlessly create and track ETL jobs using AWS Glue Studio.
• These ETL jobs use a drag-and-drop editor to perform data transformations, while AWS Glue automatically builds a code for the same. Moreover, you can monitor the progress of the ETL jobs with the AWS Glue Studio Task Execution Dashboard.

4) Explore Data with Self-Service Visual Data Preparation

• Using the AWS Glue DataBrew, you can experiment with data by directly accessing it from Data Warehouses or Databases, such as Amazon S3, Amazon Redshift, Amazon Aurora, Amazon RDS, etc.
• It also allows you to choose from 250+ in-built transformations in AWS Glue DataBrew.
• This way, you can automate various data preparation processes such as anomaly filtering, building formats, and invalid value correction.
• Once prepared, the data can be used for analytics and machine learning purposes.

5) Build Materialized Views to Combine and Replicate Data

• You can create Views using SQL in AWS Glue Elastic Views. These views are beneficial if you wish to combine data stored in multiple data sources and update it regularly. AWS Glue Elastic Views currently supports Amazon DynamoDB as a primary data source but can also integrate with other Amazon products.

Significance of AWS ETL Tools

• When you manually migrate your data, the chances of committing an error due to the dynamism of human nature increase. With the usage of AWS ETL Tools, you will migrate your data with zero data loss.
• Manually loading your data can be time-consuming, especially when you are dealing with petabytes of data and want to have real-time analysis. AWS ETL Tools help load data in real-time within minutes.
• The manual data migration process involves a high cost of training personnel to meet the basic standard requirements. AWS ETL Tools provide data migration at a low cost without any help from an expert.
• AWS ETL Tools ensure data consistency whereas manual methods may lead to inconsistency which can’t be avoided.
• AWS data integration tools are designed to handle large volumes of data. This makes them efficient for organizations with big data requirements.
• It is possible to integrate these tools with a wide range of data sources and destinations. Data integration across different environments becomes easier with this. 
• There are many ETL tools in AWS for data transformation. They contain pre-built transformations and you can also write custom scripts.

Conclusion

In this blog post, you have learned about what ETL is and the top 5 best AWS ETL Tools out there.

You have also seen the factors like use cases, pricing, Services etc., to consider when choosing among these AWS ETL Tools.

FAQ on AWS ETL Tools

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