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Data Engineering & Testing
10 Best Open Source ETL Tools for QA Teams in 2022

Open source ETL tools are an essential component of enterprise data integration. They help centralize data from multiple sources, allowing any department within an organization to access the insights they need to make data-driven business decisions. 

With many open-source ETL software systems on the market, it can be challenging to identify the right solution for business. Here’s a list of the best open-source ETL tools data experts are utilizing to support their big data management operations.   

Software Shortlist

  1. CloverDX

    Data management software great for automating ETL processes

  2. Apache Kafka

    Distributed event streaming platform able to handle high throughput data feeds

  3. KETL

    Scalable ETL software that supports multiple CPUs and 64-bit servers

  4. Logstash

    Server-side data processor with UI for pipeline monitoring

  5. Apache Camel

    Lightweight integration framework based on enterprise integration patterns

  6. Singer

    ETL tool with JSON-based data exchange format

  7. Talend Open Studio

    ETL and data integration tool with 900+ connectors

  8. Hevo Data

    No-code data pipeline solution with reverse ETL tool

  9. Pygrametl

    Python framework for ETL processes

  10. Apache NiFi

    ETL solution that utilizes encryption to secure dataflow

Comparison Criteria

Here’s what you should look for when selecting the best ETL tool for your business. 

  1. User Interface (UI): A simple drag-and-drop user interface allows ETL developers to visualize dataflows and monitor pipeline performance. 
  2. Usability: Easy-to-use platforms enable technical and business stakeholders to participate in ETL processes. 
  3. Integrations: Open-source ETL tools with a wide range of integrations and connectors can accommodate your current data sources and adapt to future changes in your ETL pipeline. 

Open Source ETL Tools: Key Features

  1. Scalability: A scalable, open-source ETL tool can effectively process large volumes of data and grow alongside your business. 
  2. Security: Encryption is a critical feature for ETL developers working in regulated industries, such as finance and healthcare, that process sensitive information. 
  3. Real-time Processing: With real-time ETL processing, developers can instantly send data through their pipeline. This feature is great for use cases where having access to real-time insights is critical, such as fraud detection or IT security. 

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Overviews Of The 10 Best Open Source ETL Tools

Here’s a brief description of each open source ETL tool to showcase each solution’s best use case, some noteworthy features, and screenshots to give a snapshot of the user interface. 

1

CloverDX

Data management software great for automating ETL processes

CloverDX is ETL software that enables developers to connect to any data source and manage various data formats and transformations. The platform offers an extensive library of customizable components that allows you to read, write, aggregate, join, and validate data. CloverDX also provides an integrated development environment where you can easily code and debug solutions for your ETL processes.

CloverDX’s automation tools help developers reduce manual data refinement tasks. Users can build automated processes to profile and validate data throughout their pipelines. These automated processes enable developers to scale ETL testing and error management to ensure business operations are aligned with high-quality data.

Pricing for CloverDX subscriptions is available upon request. While CloverDX is a commercial ETL tool, some parts of the platform are built with open source components.

2

Apache Kafka

Distributed event streaming platform able to handle high throughput data feeds

Apache Kafka is a distributed event streaming platform that combines messaging, storage, and stream processing. Users can publish and subscribe to streams of records, store streams of records in the order they’re generated, and process streams in real-time.

Organizations typically utilize Kafka to record and store events like payment transactions, shipping orders, and website activity. The tool is highly scalable and can handle complex, high throughput data feeds with low latency.

Fault tolerance is another key feature of Apache Kafka. The system replicates and distributes partitions across multiple servers, minimizing the risk of data loss if a server goes down. Users can configure the replication factor to specify how many copies of a partition are needed.

Kafka offers native integrations with over 100 event sources and event sinks, including Postgres, JMS, and AWS S3.

Kafka is available to download for free.

3

KETL

Scalable ETL software that supports multiple CPUs and 64-bit servers

KETL is an ETL solution that enables the development and deployment of data integration processes. With KETL’s scheduling manager, users can execute ETL jobs based on time or data events. KETL supports multiple data sources, including proprietary database APIs and relational and flat file sources.

The platform’s ETL engine is scalable and platform-independent, with support for multiple CPUs and 64-bit servers. This allows users to perform complex data manipulations in minimal time. Users can analyze their data processes with KETL’s performance monitoring tools, which collect statistics on historical and active ETL jobs.

KETL supports integrations with security and data management tools.

KETL is free to download.

4

Logstash

Server-side data processor with UI for pipeline monitoring

Logstash is an open-source server-side data processing tool for ingesting, transforming, and shipping raw data. The platform collects logs, transactions, events, and many other data types from nearly any source, including CRMs or e-commerce systems. Regardless of your data’s format or complexity, Logstash enables you to ease many data processes, like filtering personally identifiable information and structuring data.

Logstash operates on a pluggable framework with many input and output plugins available. Input plugins allow Logstash to ingest events from multiple sources, like files or GitHub. Logstash’s output plugins can route data to many targets, including data warehouses and cloud platforms. If Logstash doesn’t have a plugin that suits your needs, you can utilize the tool’s API to create your own.

ETL developers have complete visibility into their pipeline configurations with Logstash’s pipeline viewer UI. The interface lets you observe active Logstash nodes and deployments to monitor performance, availability, and bottlenecks.

Developers can download Logstash for free.

5

Apache Camel

Lightweight integration framework based on enterprise integration patterns

Apache Camel is a production-ready framework that enables ETL developers to integrate systems that consume or produce data. The platform is based on Enterprise Integration Patterns, allowing developers to simplify complex integrations involving microservices and the cloud. Developers have access to interfaces for EIPs, debuggers, a configuration system, and several other time-saving tools to implement enterprise integration solutions.

Camel can handle complex integration solutions due to its lightweight component-based architecture and message-oriented routing framework. It utilizes an inversion of control approach to data routing, enabling the uninterrupted flow of messages between various integration components. Users can program routes in XML, Scala, and Java.

Developers can embed Camel as a library within Spring Boot, Quarkus, application servers, and various cloud systems. Camel also offers many subprojects that deliver additional functionality, including Camel K, an integration framework that runs natively on Kubernetes, and Camel Karavan, a graphical user interface.

Apache Camel is available to download for free.

Download For Free.

6

Singer

ETL tool with JSON-based data exchange format

Singer offers a simplified way to write and collaborate on ETL scripts. The software consists of two main components, taps and targets. Taps extract data from sources, while targets send data to destinations. Users can mix and match taps and targets and send data between databases, web APIs, files, and many other systems.

Taps and targets communicate with JSON, enabling users to implement them in any programming language. With support for JSON Schema, Singer provides rich data types and rigid structure when needed.

Users can develop custom taps and targets or choose from over 50 applications readily available on Singer’s website, including Eloqua, GitHub, Oracle, and PostgreSQL. Singer applications are composed with pipes, meaning daemons and complicated plugins aren’t necessary for implementation.

Singer.io is open source and free to use.

7

Talend Open Studio

ETL and data integration tool with 900+ connectors

Talend Open Studio is a suite of open source tools that enables ETL developers to build basic data pipelines in less time. It features an Eclipse-based development environment and more than 900 pre-built connectors, including Oracle, Teradata, Marketo, and Microsoft SQL Server. The platform includes five components: Talend Open Studio for Data Integration, Big Data, Data Quality, Enterprise Service Bus (ESB), and Master Data Management (MDM).

Talend Open Studio is a great companion for many business intelligence (BI) tools. It provides several methods for converting multiple datasets into formats compatible with popular BI platforms, including Jasper, OLAP, and SPSS. Users can also glean insights directly from Talend Open Studio, which can generate basic visualizations, including bar charts.

Talend Open Studio supports integrations with several databases, including Microsoft SQL Server, Postgres, MySQL, Teradata, and Greenplum.

Talend Open Studio is free to download for all users.

8

Hevo Data

No-code data pipeline solution with reverse ETL tool

Hevo loads data from any source to your warehouse in real-time with zero coding required. The platform is highly intuitive, with a three-step setup process. As your business grows, so does Hevo. It was designed to handle millions of records per minute and automatically scales.

Businesses can transfer data from their data warehouse to any marketing, sales, and business applications with Hevo’s reverse ETL solution, Hevo Activate. The platform works on top of your existing data warehouse, so your data remains in one location. Activate also fixes data incompatibility issues between your warehouse and a target application. The tool automatically converts data types from your warehouse to match your target application.

Hevo integrates with over 100 databases, SaaS applications, and CRMs, including BigQuery, MySQL, and Salesforce.

Hevo offers free and paid subscriptions based on usage.

9

Pygrametl

Python framework for ETL processes

pygrametl is an open-source Python framework for developing ETL processes. It was designed to be an alternative to graphical BI programs while having the same ease of use. It supports CPython and Jython, enabling ETL developers to utilize existing Java code and JDBC drivers.

Developers can extract data from numerous sources available in pygrametl, such as SQL, CSV, and Pandas. Users can also define their own data sources. The platform provides filters and aggregators for transforming data. Default aggregators include AVG, Count, CountDistinct, Max, Min, and Sum.

pygrametl can load transformed data into any data warehouse that supports dimensional modeling. The system provides structures for defining fact tables and dimensions, including slowly changing and snowflaked dimensions.

Developers can download pygrametl for free.

Download Pygrametl For Free.

10

Apache NiFi

ETL solution that utilizes encryption to secure dataflow

Apache NiFi is an ETL tool that automates data flow between software systems. NiFi is scalable in that data transformation and routing can run on a single server or in clusters across multiple servers. Its drag-and-drop UI enables ETL developers to manage dataflows in real-time easily. NiFi is also highly configurable, allowing developers to create custom processors and reporting tasks.

NiFi ensures the security of your data flow by supporting secure protocols, including HTTPS and SSH. The system also embeds security at the user level by enabling two-way SSL authentication and user role management. Additionally, when users enter sensitive information into a data flow, such as their password, NiFi automatically encrypts it server-side.

Developers can extend NiFi by adding controller services, prioritizers, and customer user interfaces.

The software is free to download.

The 10 Best Open Source ETL Tools Summary

Tool Free Option Price
1
CloverDX

Data management software great for automating ETL processes

Not available

Check out CloverDX
2
Apache Kafka

Distributed event streaming platform able to handle high throughput data feeds

Not available

Check out Apache Kafka
3
KETL

Scalable ETL software that supports multiple CPUs and 64-bit servers

Not available

Check out KETL
4
Logstash

Server-side data processor with UI for pipeline monitoring

Not available

Check out Logstash
5
Apache Camel

Lightweight integration framework based on enterprise integration patterns

Download For Free.

Check out Apache Camel
6
Singer

ETL tool with JSON-based data exchange format

Free To Use

Check out Singer
7
Talend Open Studio

ETL and data integration tool with 900+ connectors

Not available

Check out Talend Open Studio
8
Hevo Data

No-code data pipeline solution with reverse ETL tool

Not available

Check out Hevo Data
9
Pygrametl

Python framework for ETL processes

Download Pygrametl For Free.

Check out Pygrametl
10
Apache NiFi

ETL solution that utilizes encryption to secure dataflow

Not available

Check out Apache NiFi

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Other Options

Here are a few more ETL tools that didn’t make the top list.

  1. Pentaho Kettle – ETL solution that utilizes the Maven framework 
  2. Scriptella – Java-based ETL and script execution software 
  3. Bubbles – Python ETL framework for processing, auditing, and inspecting data
  4. Petl – Tentative Python package for building simple ETL pipelines

What are ETL tools?

ETL tools facilitate raw data extraction, transformation, and loading into a centralized location, like a data warehouse. ETL systems also enable multiple types of data to work together, making them essential data integration tools. The three-step ETL process is critical in helping businesses ensure their data is high-quality and optimized for operations such as analytics, data science, machine learning, and artificial intelligence. 

What do you think about this list?

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By The QA Lead Team

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