Finding the correct ETL (Extract, Transform and Load) tool for your business is essential as they help you unify and enrich data from numerous data sources, allowing you to carry out an insightful analysis & gain actionable insights from your customers. Searching for these ETL tools can be a tedious task and requires long hours of research. It also requires companies to have clear, well-established goals to find the tool that best fits their requirements.
In today’s world, Open-Source ETL Tools have gained more popularity compared to other ETL Tools. This is because Open-Source ETL Tools help businesses keep their costs low but provide similar functionalities as other ETL Tools. Open-Source ETL Tools provide a simple and accurate UI (User Interface) and help all types of users set up the ETL process within a few minutes.
This article provides you a comprehensive list of the Top 11 Popular Open-Source ETL Tools and describes their features and pricing models briefly, along with few limitations of leveraging these tools. It also outlines the ETL process in detail to help companies choose the best tool according to their business goals. Read along to find out about these amazing tools.
Table of Contents
- Introduction to the ETL Process
- 4 Key Features of Open-Source ETL Tools
- Top 11 Popular Open-Source ETL Tools
- Limitations of Open-Source ETL Tools
- Working knowledge of SaaS applications.
- Working knowledge of Open-Source and Cloud Environments.
Introduction to the ETL Process
The Modern Data Analytics Stack leverages the ETL process to extract data from data sources such as Social Media Platforms, Email/SMS services, Customer Service Platforms, Surveys, and a lot more to help gain valuable and actionable customer insights or to store the data in Data Warehouses. The ETL process consists of 3 steps:
- Extraction: Extraction is an essential part of the ETL process as it helps unify Structured and Unstructured data from a diverse set of data sources such as Databases, SaaS applications, files, CRMs, etc. Extraction Tools simplify this process by allowing users to extract valuable information in a matter of a few clicks. All this is done without having to write any complex code.
- Transformation: Transformation is the process of converting the extracted data into a common format so that it can be better understood by a Data Warehouse or a BI (Business Intelligence) tool. Some transformation techniques include Sorting, Cleaning, Removing Redundant Information, and Verifying the Data from data sources.
- Loading: Loading is the process of storing the transformed data into a destination, normally a Data Warehouse, and also supports analysis of the data using various BI tools to gain valuable insights and build reports and dashboards. The Loading stage is crucial as the customer data is visualized using different BI tools after this stage.
The given figure highlights the stages of the ETL process:
4 Key Features of Open-Source ETL Tools
Open-Source ETL Tools have gained popularity because they are work-in-progress tools that do not provide many features in other ETL Tools but get regularly updated. Being Open-Source enables these tools to be constantly monitored by a large number of tester’s to improve and accelerate the development of the tools. Along with being significantly less expensive than commercial products, Open-Source ETL Tools help expand the research, visibility, and developmental domains.
The 4 Key Features of Open-Source ETL Tools are:
- Embeddable Data Integration
- Inexpensive Integration Tooling
- Local Solution
- Smaller Budgets & Fewer Complex Requirements
1) Embeddable Data Integration
When Independent Software Vendors (ISV) look for Embeddable Data Integration, they opt for Open-Source ETL Tools. This is because these tools provide services for Data Integration, Migration, and Transformations at decent costs, along with comparable performance in comparison to commercial products.
2) Inexpensive Integration Tooling
When System Integrators (SI) look for Inexpensive Integration Tooling, Open-Source ETL Tools come into their mind. These tools enable System Integrators to integrate data significantly quicker and with higher quality as compared to commercial products.
3) Local Solution
Enterprise Departmental Developers that want to find local solutions opt for Open-Source ETL Tools.
4) Smaller Budgets & Fewer Complex Requirements
Companies that do not have complicated requirements tend to opt for Open-Source ETL Tools. This is because these tools accomplish business requirements while keeping their budgets in check.
Best Open-Source ETL Tools
Here’s a list of some the best Open-Source ETL Tools available in the market, that you can choose from, to simplify ETL. Selecting the right tool for your business needs has never been this easy:
Top 11 Popular Open-Source ETL Tools
Choosing the best Open-Source ETL Tool for your business requirements can be a daunting task as each tool has its advantages and disadvantages. Generally, companies would like to opt for tools that are regularly monitored by the community and bring in new features too. Here is a comprehensive list of the Top 11 Popular Open-Source ETL Tools:
1) Hevo Data
Hevo Data, a No-code Data Pipeline helps to load data from any data source such as Databases, SaaS applications, Cloud Storage, SDK’s, and Streaming Services and simplifies the ETL process.Get Started with Hevo for Free
It supports 100+ data sources (Including 30+ Free Data Sources) and is a 3-step process by just selecting the data source, providing valid credentials, and choosing the destination. Hevo not only loads the data onto the desired Data Warehouse but also enriches the data and transforms it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
Check out what makes Hevo amazing:
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
Hevo Data provides users with three different subscription offerings, namely, Free, Starter and Business. The free plan houses support for unlimited free data sources, allowing users to load their data to a data warehouse/desired destination for absolutely no cost! The basic Starter plan is available at $249/month and can be scaled up as per your data requirements. You can also opt for the Business plan and get a tailor-made plan devised exclusively for your business. Hevo Data also provides users with a 14-day free trial. You can learn more about Hevo Data’s pricing here.
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2) Apache Camel
Apache Camel is an Open-Source framework that helps you integrate different applications using multiple protocols and technologies. It helps configure routing and mediation rules by providing a Java-object-based implementation of Enterprise Integration Patterns (EIP), declarative Java-domain specific language, or by using an API.
Apache Camel uses more than 100 components including FTP, JMX, and HTTP. It uses Uniform Resource Indicators (URI) to provide information such as which components are being used, the context path, and which options are applied on what components.
Airbyte is one of the newest Open-Source ETL Tools that was launched in July 2020. It differs from other ETL tools as it provides connectors that are usable out of the box through a UI and API that allows community developers to monitor and maintain the tool.
The connectors run as Docker containers and can be built in the language of your choice. By providing modular components and optional feature subsets, Airbyte provides more flexibility.
Currently, Airbyte has 3 pricing models: Community, Standard, and Enterprise depending on the number of connectors, the number of seats needed and the number of premium features activated.
4) Apache Kafka
Apache Kafka is an Open-Source Data Streaming Tool written in Scala and Java. It publishes and subscribes to a stream of records in a fault-tolerant manner and provides a unified, high-throughput, and low-latency platform to manage data.
Apache Kafka can be used as a message bus, a buffer for systems and events processing, and to decouple applications from databases for both OLTP (Online Transaction Processing) and Data Warehouses.
Logstash is an Open-Source Data Pipeline that extracts data from multiple data sources and transforms the source data and events and loads them into ElasticSearch, a JSON-based search, and analytics engine. It is part of the ELK Stack. The “E” stands for ElasticSearch and the “K” stands for Kibana, a Data Visualization engine.
It is written in Ruby and is a pluggable JSON framework that consists of more than 200 plugins to cater to the ETL process across a wide variety of inputs, filters, and outputs. It can be used as a BI tool or even as a Data Warehouse.
Currently, Logstash is part of ElasticSearch and comes in 4 pricing packages, namely Standard, Gold, Platinum, and Enterprise. The Standard edition is $16 per month, the Gold edition is $19 per month, the Platinum edition is $22 per month and the Enterprise edition is $30 per month.
6) Pentaho Kettle
Pentaho Kettle is now a part of the Hitachi Vantara Community and provides ETL capabilities using a metadata-driven approach. It has a graphical drag and drop UI and standard architecture. This tool allows users to create their own data manipulation jobs without writing a single line of code. Hitachi Vantara also offers Open-Source BI tools for reporting and Data Mining that work seamlessly with Pentaho Kettle.
Currently, Pentaho Kettle provides a 30-day free trial period. The exact pricing details are not disclosed.
7) Talend Open Studio
Talend Open Studio is a free and Open-Source ETL Tool that provides its users a graphical design environment, ETL and ELT support, and enables them to export and execute standalone jobs across runtime environments. It has a wide range of connectors for RDBMS, SaaS, Packaged applications, Dropbox, LDAP, FTP, and many more. It also offers Open-Source solutions for Data Preparation and Data Quality.
Currently, Talend offers 5 pricing models. These include Talend Open Source (Free for everyone), Stitch Data Loader (Free 14-Day Trial), Talend Pipeline Designer (Free 14-Day Trial), Talend Cloud Data Integration (Free 14-Day Trial), and Talend Data Fabric (Contact Sales).
Some Open-Source ETL Tools have a command line interface. Singer is one such tool that uses a command-line interface to allow users to build modular ETL Pipelines using its “Tap” and “Target” modules. Singer provides a framework that allows users to connect data sources to storage locations directly.
With a large collection of pre-built taps, scripts can be defined for ETL processes and users can write concise, single-line ETL processes that can easily be modified by swapping taps and targets.
KETL is a production-ready ETL platform designed to assist the development and deployment of Data Integration processes. It allows users to use an Open-Source platform to manage complex data. The KETL engine consists of a multi-threaded server to manage different job executors. Job executors fall into several categories including SQL, OS, XML, Sessionizer, and Empty.
10) Apache NiFi
Apache NiFi allows you to automate and manage the flow of information systems. It also enables NiFi to be an effective platform for building scalable and powerful dataflows. NiFi follows the fundamental concept of Flow-Based Programming. It has a highly configurable web-based UI, and houses features such as Data Provenance, Extensibility, and Security features.
The pricing details of Apache NiFi depend on the configuration costs you want. It can be purchased in the AWS Marketplace. The Professional edition costs $0.25 per hour if you purchase it with an AWS account.
CloverDX is one of the first Open-Source ETL Tools. It has a Java-based Data Integration framework that is designed to transform, map and manipulate data of various formats. It can be used as a standalone system or be embedded with other databases and files such as RDBMS, JMS, SOAP, HTTP, FTP, and many more.
Although CloverDX is no longer offered by the provider, you can download it from this link.
Currently, CloverDX has 2 pricing models, CloverDX Designer and CloverDX Server. Each has a 45-day trial period and fixed prices after the trial are completed. You can talk to CloverDX Tech Support in case you face any issues.
Limitations of Open-Source ETL Tools
Although Open-Source ETL Tools can provide a solid backbone for your Data Pipeline, they have few limitations especially when it comes to providing support. As these tools are work-in-progress tools many of them are not fully developed and are not compatible with multiple data sources. Some of the limitations of Open-Source ETL Tools include:
- Enterprise Application Connectivity: Companies are not able to connect a few of their applications with Open-Source ETL Tools.
- Management & Error Handling Capabilities: Open-Source ETL Tools are not able to handle errors easily due to their lack of error handling capabilities.
- Non-RDBMS Connectivity: Some Open-Source ETL Tools are not able to connect with a variety of RDBMS and can hamper the performance of the Data Pipeline when data is collected from these data sources.
- Large Data Volumes & Small Batch Windows: Some Open-Source ETL Tools need to analyze large data volumes but can process the data in small batches only. This can reduce the efficiency of the Data Pipeline.
- Complex Transformation Requirements: Companies that have complex transformation needs cannot use Open-Source ETL Tools. This is because they often lack support for performing complex transformations.
- Lack of Customer Support Teams: As Open-Source ETL Tools are managed by communities and developers all around the world, they do not have specific customer support teams to handle issues.
- Poor Security Features: Being Open-Source causes these tools to have poor security infrastructure and become prone to many cyber attacks.
This article gave a comprehensive list of the Top 11 Open-Source ETL Tools. It also provided you a brief overview of the ETL process. It further explained the features and pricing models for a few of the tools. Finally, it highlighted some of the limitations of these tools. Overall, Open-Source ETL Tools play a pivotal role in the field of Data Analytics today due to their regular development and cheaper prices. Paid ETL Tools are also important as they provide better features and insights from their customers. At the end, whether you opt for a Paid ETL Tool or an Open-Source Tool, you can be rest assured that the quality of your data will never get compromised.
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