ETL is a term that stands for Extract, Transform, and Load. It’s a data integration service that brings together data from several sources into a single, consistent data store, which may subsequently be fed into a Data Warehouse or other destination system.
There are a plethora of ETL Tools in the market that can make Data Management easier while also boosting Data Warehousing. We’ll look at a few open-source free tools as well as a few commercial, licensed solutions in this post to see whether they may help you achieve your business needs.
Best ETL Tools for 2022
1. Hevo Data
Hevo is a data pipeline platform that doesn’t require any programming and is fully managed, making it simple to integrate and load data from 100+ different sources in real-time to a destination of your choice.
Hevo is simple to set up and allows users to swiftly load data without compromising performance. Its extensive connectivity with a variety of sources enables users to easily import data of various types without having to write a single line of code.
Hevo’s features include being totally automated, having a scalable infrastructure, supporting real-time data, 24/7 Live Support, supporting transformations and providing various connectors, Live Monitoring, 100% Complete & Accurate Data Transfer, and Schema Management.
You can sync data from 100+ sources to your destinations using Hevo’s no-code data pipeline platform. Know more about Hevo Integrations.
2. Informatica PowerCenter
Informatica PowerCenter is an enterprise Data Integration solution that is high-performance and scalable and covers the entire data integration process. PowerCenter may offer data on-demand in batch, real-time, or Change Data Capture formats (CDC).
The following are some of Informatica PowerCenter’s primary features:
- Informatica PowerCenter makes creating Data Marts and Data Warehouses a breeze.
- Some of the features that assist it to meet scalability, security, and collaboration requirements include Metadata Management, High Availability, Data Masking, and Dynamic Partitioning.
3. IBM Infosphere DataStage
IBM Infosphere DataStage is an ETL tool that is part of IBM’s Infosphere and IBM Information Platforms Solutions package. It uses a graphical notation to design Data Integration solutions.
The following are some of the key characteristics of IBM Infosphere DataStage:
- IBM Infosphere DataStage is a batch-processing ETL tool.
- With IBM Infosphere DataStage, you can easily separate ETL job design from execution.
- You can do any job thirty percent faster with a parallel engine and also workload balancing.
4. Talend
Talend enables you to manage every stage of the Data Lifecycle and provides you with access to clean data. Data Integration, Data Integrity, Governance, API, and Application Integration are all services provided by Talend.
The following are some of Talend’s important features:
- Talend Studio includes a graphical user interface for creating flow and transformation algorithms.
- It supports most on-premise and cloud databases and links to a range of software as a service offerings.
- Talend’s functions are carried out via a code generation approach. This means that the code must be rebuilt every time the logic changes.
5. Pentaho
Pentaho is a prominent Business Intelligence software that includes data integration, reporting, OLAP, data mining, ETL capabilities, and information dashboards. Pentaho can be used to convert complex data into useful reports and extract information from them.
The following are the main characteristics of Pentaho:
- It makes use of hybrid and multi-cloud systems.
- It’s designed for batch ETL use cases on-premise.
- Pentaho is based on XML-formatted ETL methods being interpreted. Pentaho surpasses some of its competitors due to the lack of code generation.
6. AWS Glue
AWS Glue is a serverless ETL service that sifts through your data and conducts Data Preparation, Data Ingestion, Data Transformation, and Data Catalog building.
AWS Glue has the following main features:
- AWS Glue is mostly batch-oriented, although it can also handle Lambda-based near-real-time scenarios.
- It may construct a serverless full-fledged ETL Pipeline using AWS Glue and Lambda functions.
- It has a pay-as-you-go pricing approach where you pay an hourly amount and are billed by the second.
- AWS Glue has two significant features which are an integrated Data Catalog and automatic schema discovery.
7. SAS Data Integration Studio
SAS Data Integration Studio is a visual design tool for executing and building various Data Integration processes. It can perform these tasks regardless of the data sources, platforms, or applications used. The following are some of SAS Data Integration Studio’s primary features:
- Its customized metadata tree makes it easy to analyze, display, and comprehend data.
- It provides a specialized GUI for data profiling, making it easier to fix source system issues while keeping the business issues for use in any Data Management process.
- During development, SAS Data Integration Studio also provides interactive testing and debugging of jobs.
8. Google Data Flow
Google Data Flow is a fully managed service that can be to run Apache Beam Pipelines in the Google Cloud environment. The following are some of Google Data Flow’s important features:
- Because Data Flow’s serverless solution minimizes operational overhead from Data Engineering tasks, you can focus on programming rather than managing server clusters.
- It also has Resource Autoscaling and cost-optimized Batch Processing capabilities.
- Google Data Flow’s real-time AI capabilities enable near-human intelligence real-time reactions to big events.
9. Apache Nifi
The purpose of Apache Nifi was to automate data flow across systems. Nifi runs on the Java Virtual Machine(JVM) of the host operating system. The following are some of Apache Nifi’s important features:
- The Apache Nifi architecture enables developers to construct a highly concurrent model without worrying about concurrency issues in general.
- It also encourages the creation of loosely coupled and cohesive components that may be reused in different circumstances, as well as the production of testable units.
10. Azure Data Factory
Azure Data Factory is a fully managed serverless data integration solution. Even if you have no prior coding knowledge, Azure Data Factory makes it simple to create ETL procedures in an intuitive environment.
Some of Azure Data Factory’s key features are listed below:
- With over 90 built-in connectors, Azure Data Factory can ingest all of your Software as a Service (SaaS) and software data.
- Azure Data Factory can rehost SQL Server Integration Services in a few clicks thanks to built-in CI/CD and Git support.
Conclusion
This blog analyzed the top 10 ETL tools in the market right now. You can use one of them as per your use case and budget to boost your production through a significant increase in operational efficiency, depending on your needs.
Also, you can get to know more ETL tools in this blog.
