EVL – a developer friendly code based ETL

EVL is a code based ETL (Extract-Transform-Load) that gives the ETL developer the power to solve complex problems by keeping the simple things simple, and splitting complex processing into simpler steps.

Use cases

  • Staging data – We provide predefined generic jobs for staging, including getting data definitions from DBMS and csv files, with switches like “incremental/delta/full load”, SCD2 historization, etc.
  • Move SQL into ETL – Replace DBMS processing by much cheaper ordinary Linux machine processing. We provide SQL2EVL script which automates most of the job.
  • Replace heavy ETL – For some ETL tools we provide migration scripts, which make migrations straightforward.
  • Data Marts – High performance joins and aggregations are suitable to prepare data for Data Marts.
  • Data ingestion – We provide generic jobs for data ingestion, including data masking (salt, encription, hash), enriching by lookup, etc.
  • Spark code generator – EVL jobs can wrap Spark template code. Use the power of Spark, while keeping the solution design clear and easily debuggable.
  • High performance JSON parsing – Filter/mask/cleanse your data immediately on Edge node.
  • Parquet producer – Generate this columnar file format immediately from sources, including partitioning.
  • Move processing to Edges – EVL is light, suits any Linux installation even those with limited resources.
  • Stream data processing – Kafka, Flume, or any other streams or queues can be switched (i.e. consumed-modified-produced) by EVL.



The ETL tool itself. EVL jobs can be run from command line, by EVL Workflow, or any other scheduler and/or job manager.

Available in:

  • Community Edition
  • Enterprise Edition

EVL Workflow

A job manager, which orchestrates EVL jobs, or any other command line command. Can be used standalone, no need for an EVL installation.

Available in:

  • Enterprise Edition


EVL Manager

Web user interface to monitor and manage EVL jobs and EVL Workflows.

Available in:

  • Enterprise Edition


References and Testimonials

T-Mobile Czech Republic a.s. decided to change their European Data Warehouse data processing and management platform from a traditional relational database and ETL tool to a big data ecosystem. The decision was driven by increased pressure for shorter time-to-market and the quicker pace of industry changes. To address those challenges Deutsche Telekom has not only been selecting new technologies, but also adopting an agile methodology. In the course of project, EVL significantly outperformed an originally selected semi-open source ETL tool; this high performance and outstanding productivity helped Deutsche Telekom achieve their objectives.

With EVL Tool we finished our data migration project ahead of schedule, with savings in both our project and operational budgets.

Eva Mikulecka
OSS/BSS Integration Services Project Manager

High productivity, processing performance, and a flexible collaborative mode made us select EVL as our preferred ETL platform for data integration and big data projects.

Ondrej Machacek
Architecture&Integration Senior Manager