ETL collects and redefines data, and delivers them to a data warehouse

ETL stands for 'extract, transform and load.' The process of ETL plays a key role in data integration strategies. It is the process of moving raw data from one or more sources into a destination data warehouse. ETL allows businesses to gather data from multiple sources and consolidate it into a centralized location. This is essential in making the data analysis-ready in order to have a seamless business intelligence system in place.

ETL collects and redefines different types of data, and delivers them to a data warehouse such as Redshift, Azure or BigQuery. The system makes it possible to migrate data between a variety of sources, destinations and analysis tools. Ultimately, ETL process produces business intelligence and executing broader data management strategies.

ETL tools are applications or platforms that help businesses move data from one or many disparate data sources to a destination. These tools aid making data both comprehensible and accessible in the desired location, namely a data warehouse. Selecting a good ETL tool is important in the process. An ETL tool automates most of the workflows in a company without needing human intervention. It also provides a highly available service. Henceforth, choosing a perfect ETL plays a vital role in future use cases.

Here are the top ETL tools that could make users job easy with diverse features

Hevo Data

Hevo Data is an easy learning ETL tool which can be set in minutes. Hevo moves data in real-time once the users configure and connect both the data source and the destination warehouse. The tool involves neither coding nor pipeline maintenance. Hevo provides connectivity to numerous cloud-based and on-site assets.

The automatic detection and mapping of schema from the incoming data minimises the manual configuration work in the process. Hevo also provides a simple Python interface to clean, transform and enrich data before moving it to the warehouse.

Informatica PowerCenter

Informatica PowerCenter facilitates an on-premise ETL tool that can work with a number of traditional database systems. The tool has comprehensive support for data governance, monitoring, master data management and data masking. ETL is a primary batch-based ETL tool that has a cloud counterpart which allows accessing repositories deployed inside the organisation's premises. It also supports a variety of data storage solutions and software as a service offering.

IBM InfoSphere DataStage

IBM InfoSphere DataStage is an enterprise product aimed at bigger organizations with legacy data systems. This is also a primary batch-based tool with a cloud version that can be hosted in the IBM Cloud. The focus is on-premise databases and executing the transformation tasks in the cloud. IBM data stage has connectors to cloud-based data storage solutions like AWS S3 and Google cloud storage. Since it supports JDBC, software as a service data warehouses like Redshift which provides JDBC connectors can also be integrated.

Talend

Talend tool features a large suite of products ranging from data integration to big data management, data protection and more. Talend Data Fabric is a collection of all tools that come under the Talend Umbrella bundled with platinum customer support. Talend Open Studio is open-source that can be used without paying if you do not use Talend Cloud. The tool supports most cloud and on-premise databases. It has connectors to software as a service offering as well.

Pentaho

Pentaho, also known as Kettle is an open-source community and an enterprise edition. The tool is also built to cater at on-premise with data integration and processing features from a diverse set of data sources. Pentaho bets heavily on the hybrid cloud and multi-cloud based architectures. It interprets the ETL procedures stored in XML format.

AWS Glue

Provided by AWS, Glue is a cloud-based real-time ETL tool. It supports use cases based on lambda functions. AWS Glue has some notable features such as integrated data catalogue, automatic schema discovery, etc. AWS Glue combined with lambda functions allows it to implement a serverless full-fledged ETL pipeline.

StreamSets

StreamSets is a DataOps tool that has data monitoring capabilities that stretch beyond the traditional ETL. It is a cloud-optimized real-time tool. StreamSets utilizes a spark-native execution engine to extract and transform data. Customers can build batch and real-time data pipelines with minimal coding. The tool supports a large number of origin and destination combinations.

Blendo

Blendo is the leading ETL and data integration tool to simplify the connection of data sources to databases. It automates data management and data transformation to get to Business Intelligence insights faster. Blendo focuses on extradition and syncing of data. It extracts raw data from sources and loads it into destinations without performing transformations.

Google Cloud Dataflow

Google cloud dataflow is a fully managed ETL service provided by Google based on Apache Beam. Using Dataflow, it is possible to run a completely serverless ETL pipeline based on google ecosystem components. Google cloud platform complies with all data security guidelines like HIPAA and GDPR. The tool works well for both batch and real-time use cases.

Azure Data Factory

Azure Data Factory is a hybrid data integration service developed by Microsoft to simplify ETL at scale. By integrating data silos with Azure Data Factory, it unveils a service built for data integration needs and skill levels. Data factory can run a completely serverless ETL pipeline using Azure components. Azure data factory is not suited for multi-cloud or hybrid cloud-based architectures.