The best programming language for ETL processes depends on various factors like the specific project requirements, data sources involved, the team's expertise, and the existing technology stack. A few of the most commonly used programming languages for ETL include: Python: Python offers powerful libraries and ETL tools like Pandas, NumPy, and SQLAlchemy for data manipulation, transformed data, and database connectivity. SQL: SQL is well-suited for handling data extraction, transformation, and loading tasks involving SQL-based databases. It provides powerful querying capabilities, efficient data manipulation operations, and optimized database features. Java: Java offers mature frameworks like Apache Beam, Spring Batch, and Apache Camel which provide extensive support for ETL workflows, data integration, and parallel data processing.  Scala: Scala is a statically typed programming language that runs on the Java Virtual Machine (JVM) and integrates with Java. Scala is widely used with Apache Spark, a popular big data processing framework. HTML: While HTML is not an ideal choice for ETL actions, it can be a component of the data extraction phase when working with web-based data sources. HTML parsing and web scraping techniques enable the extraction of relevant data from web pages. This data can then be processed and loaded into the desired format using ETL tools or other programming languages. Learn about migrating to a modern workload automation solution with ActiveBatch.