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  1. DZone
  2. Data Engineering
  3. Big Data
  4. Open-Source ETL Tools Comparison

Open-Source ETL Tools Comparison

For all of your extraction, transformation, and loading needs, here is a helpful list of open source ETL tools to compare.

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Garrett Alley user avatar
Garrett Alley
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May. 14, 18 · Review
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Open source data integration tools can be a low-cost alternative to commercial packaged data integration solutions. And just like commercial solutions, they have their benefits and drawbacks.

If you do not have the time or resources in-house to build a custom ETL solution — or the funding to purchase one — an open source solution may be a practical option. Further, open source ETL solutions can be a great fit for smaller projects, or places where data analysis is not mission critical. Keep in mind that most open source ETL solutions will still require some configuration and setup work (if not actual coding). So even if you avoid having to hand code a solution, you still may need to have some systems or programming expertise available.

Open-Source ETL Tools Overview

Open source implementations play an important role in the world of ETL, helping to further research, visibility, and developmental standards. Open source communities include a large number of testers which can help improve and accelerate the tools' development. Some people prefer to only use open source solutions. Of course, the most notable feature of open source ETL products is that they are often significantly less expensive than commercial solutions.

The four basic constituencies that typically adopt open source ETL tools are:

  • Independent software vendors (ISV) looking for embeddable data integration — costs are reduced and the savings are passed on customers; data integration, migration and transformation capabilities are incorporated as an embedded component; memory footprint of the end product is reduced in comparison to large commercial offers
  • System integrators (SI) looking for inexpensive integration tooling — open source ETL software allows system integrators to deliver integration capabilities significantly faster and with a higher quality level than by custom building the capabilities
  • Enterprise departmental developers looking for a local solution — using the free ETL tools technology by larger enterprises to support smaller initiatives
  • Mid-market companies with smaller budgets and less complex requirements — small companies are more likely to support open source ETL providers as they have less demanding needs for data integration software

While some open source projects specialize in a single ETL or data integration function (some tools may support extracting data only, others might only serve to move data, for example), a number of open source projects are capable of performing a wider set of functions.

Popular Open-Source ETL Tools

This is not an exhaustive list, but it does cover many of the popular offerings.

Apache Airflow

Apache Airflow is a project that builds a platform offering automatic authoring, scheduling, and monitoring of workflows. Workflows are authored as directed acyclic graphs (DAGs) of tasks. The scheduler executes tasks on arrays of workers and follows dependencies as specified. The command line utilities allow users to perform surgeries on DAGs, and the user interface allows users to visualize production pipelines, monitor progress, and troubleshoot issues.

Open Source version is limited: No

Apache Kafka

Apache Kafka is a distributed streaming platform that offers publish and subscribe to streams of records (similar to a message queue), supports fault-tolerant storing of streams of records, and allows processing streams of records as they occur.

Kafka is typically used for building real-time streaming data pipelines that either move data between systems or applications, or transform or react to the streams of data. The core concepts of this project include running as a cluster on one or more servers, strong streams of records in categories (or topics), and working with records, where each record includes a key, a value, and a timestamp. Kafka has four core APIs: the Producer API, the Consumer API, the Streams API, and the Connector API.

Open Source version is limited: No

Apache NiFi

The Apache NiFi project is used to automate and manage the flow of information between systems, and its design model allows NiFi to be a very effective platform for building powerful and scalable dataflows. NiFi's fundamental design concepts are related to the central ideas of Flow-Based Programming. The main features of this project include a highly configurable web-based user interface (for example, including dynamic prioritization and allowing back pressure), data provenance, extensibility, and security (options for SSL, SSH, HTTPS, and so on).

Open Source version is limited: No

CloverETL

CloverETL offers an open source/community version of its engine. The engine is a Java library and does not include any visualization or UI components. It does, however, include access to ETL/Data transformation features used in the commercial version.

CloverETL's Community Edition offers a visual tool with basic data transformation capabilities to the general community at no cost. It permits execution of data transformations at full speed, but it includes a fairly limited set of transformation components.

Open Source version is limited: Yes

Jaspersoft

Jaspersoft data integration software extracts, transforms, and loads data from different sources into a data warehouse or data mart for reporting and analysis purposes. The community version is available as open source.

Open Source version is limited: Yes

KETL

According to its SourceForge page, KETL is a production-ready ETL platform and its engine is built upon an open, multi-threaded, XML-based architecture. The product is designed to assist in the development and deployment of data integration efforts which require ETL and scheduling. It appears to have been last updated in 2015.

Open Source version is limited: No

Pentaho Kettle

Pentaho Kettle is the component of Pentaho responsible for the ETL processes. It enables users to ingest, blend, cleanse, and prepare diverse data from any source. Pentaho also includes in-line analytics and visualization tools. This community version is free, but offers fewer capabilities than the paid version.

Open Source version is limited: Yes

Talend Open Studio

Talend offers Open Studio for Data Integration as a limited-functionality open source (Apache license) version of its Data Management Platform. It offers connectors for various RDBMS, SaaS, packaged apps, and technologies.

Open Source version is limited: Yes

Limitations of Open-Source ETL Tools

When used appropriately, and with their limitations in mind, today's free ETL tools can be solid components in an ETL pipeline.

It should be noted that these offerings are continuously improved, just as most commercial products. The current drawbacks for open source ETL tools include limited support for:

  • Enterprise application connectivity
  • Robust management and error handling capabilities
  • Non-RDBMS connectivity
  • Change data capture (CDC)
  • Integrated data quality management and profiling
  • Large data volumes and small batch windows
  • Complex transformation requirements

Even so, many customers are not looking for large and expensive data integration suites. Consider open source ETL technologies where they can be an efficient and reliable alternative to the time consuming and error prone approach of custom coding data integration requirements.

The most popular open source vendors are still not truly community-driven projects. This may be an issue going forward as the number and complexity of data sources continue to increase. More investment is needed, from a wider community, to build out and encourage the development of open source ETL tools. Note also that often the open source versions are feature-limited versions of commercial products. In the end, you may trade features for lower cost, or you may have to do more configuration and setup to have the features you want and still maintain an open source approach.

The open source tools and solutions listed above may not be able to solve the complex, dynamic problems faced by today's data-dependent enterprises. A true solution needs to handle not only the vast array of data sources that currently exist, but those that are being created every day. This tsunami of data could overwhelm under-sized implementations.

Modern ETL Solution

A modern ETL solution requires a modern ETL platform: a system that supports importing a vast array of enterprise on-prem and web-based data sources into your cloud data warehouse. New data sources (various social media, marketing, and monitoring services, for example) are becoming available constantly, so modern ETL solutions need to be flexible and well-maintained/tested. They need to be able to handle schema changes and structured and semi-structured data.

Alooma's easy-to-use data pipeline as a service provides a data streaming platform to support both batch and high volume real-time, low-latency data integration requirements. Alooma's flexible enrichment capabilities enable advanced and complex data preparation and enhancement of any data source before loading into any data warehouse. Alooma's platform includes the Restream Queue to handle errors and ensure data integrity.

Ready to start? Get your ETL pipeline up and running in minutes with Alooma.

Open source Extract, transform, load Data integration kafka Comparison (grammar)

Published at DZone with permission of Garrett Alley, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • Optimizing Your Data Pipeline: Choosing the Right Approach for Efficient Data Handling and Transformation Through ETL and ELT
  • Evaluating Message Brokers
  • CRM Analytics Data Flow and Recipe, Ultimate Guide to Data Transformation
  • How to Create — and Configure — Apache Kafka Consumers

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