What are common ETL tools used in the industry?

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In today’s data-driven companies, ETL (Extract, Transform and loads) tools are essential for building robust and scalable data pipelines. They facilitate everything from taking raw data from multiple sources, turning it into usable formats and then placing it in data lakes or data warehouses. Below are the most commonly used ETL tools in use in the industry today, and their strengths. Then, we’ll discuss the ways in which their use is connected to education in data engineering which includes the data engineering course at Pune and the course curriculum.

Common ETL Tools used in the industry
Apache Airflow Apache Airflow is an extensively used free workflow automation platform. It is not an ETL tool that is used primarily to plan and manage data pipelines by creating Directed Acyclic Graphs (DAGs) in Python. Airflow’s strength is its ability to be used to trigger, monitor and manage the data’s extraction and transformation and loading tasks. It also integrates with other tools, such as Spark, dbt or cloud services.

Apache NiFi
for real-time streaming or live data flow, Apache NiFi is a top option. It provides a drag-and drop flow-based UI that allows backpressure, data provenance and provides powerful routing transformation, data-flow, and mediation capabilities for the system. Syllabus

dbt (Data Build Tool)
dbt is a transformation-focused open-source tool built for analytics engineering. Its premise can be described as “ELT” (Extract the data, load it Transform) It loads unstructured data in your warehouse initially before using dbt transform it with SQL. It allows the control of version and modular SQL testing, version control, and documentation.

AWS Glue
AWS Glue is Amazon’s ETL serverless service. It’s tightly integrated into AWS services such as S3, Redshift, and Athena. Glue is able to automatically identify different data schemas (using crawlers) and then can scale up or down according to the need. This makes it a great choice for teams operating in AWS. AWS ecosystem.

Azure Data Factory (ADF)
ADF is Microsoft’s cloud-based managed ETL, data integration, and platform. It can support both pipelines that are code-free (via drag-and-drop) as well as code-based data flows. ADF can also support hybrid (on-prem and cloud) integration, which makes it a flexible tool.

Informatica PowerCenter
Informatica PowerCenter has been a standard in large organizations for traditional ETL tasks. It provides robust governance metadata management and scalability and has been tested in large enterprises that have strict compliance requirements.

IBM InfoSphere DataStage
A powerful tool for enterprise-scale ETL, DataStage supports parallel processing as well as real-time and batch integration, as well as strong metadata management. DataStage is commonly employed in large data warehouse projects.

Talend
Talend is a tool for data integration that is available in both open source and enterprise versions. It can be used for real-time or batch ETL and data quality management, and comes with an intuitive, low-code visual interface.

Fivetran
Fivetran is a fully-managed, cloud-based ELT tool. It offers a wide range of connectors for various SaaS applications, databases, as well as other systems. It handles the changes to schemas and versions automatically.

Scriptella
for ETL that is lighter weight or script-based, Scriptella is an open-source program that is written in Java. It doesn’t come with an GUI however, ETL logic is expressed in XML and SQL and other Scripting Languages. This makes it suitable for small or minor database migration tasks.

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