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DataCleaner
What it is
DataCleaner is a free, open source data quality solution for profiling, cleansing, and validating data. Its profiling engine can identify patterns, missing values, character sets, and other characteristics of data values. It works with CSV files, Excel spreadsheets, relational databases, and NoSQL databases. Users can build cleansing rules with search and replace, regular expressions, pattern matching, or custom transformations, and check values against internal or external reference data. The project names Apache Hadoop, Apache Spark, Pentaho Data Integration, and Apache MetaModel among its integrations or connectivity options. Developers can embed DataCleaner in other applications or build plugins for specific use cases. The project also describes community-driven extensions, integrations, and shared content. It supports batch processing, visual workflows, standardization, enrichment, and scheduled runs, with desktop deployment for Linux, macOS, and Windows. The code is licensed under the Lesser General Public License (LGPL). The downloads page lists community edition 5.9.0 as the latest release; release news lists version 5.8.1 dated February 9, 2022 and says it runs on Java versions 9 through 17.
For and against
For
- Works with CSV, Excel, relational, and NoSQL sources.
- Cleansing rules can use patterns or custom transformations.
- Can compare values against reference data.
- Free and licensed under LGPL.
Against
- Latest listed release is community edition 5.9.0.
- Release news lists version 5.8.1 dated February 9, 2022.
- Deployment is desktop.
The verdict
DataCleaner combines profiling and configurable cleansing for data from several file and database types. Its integrations and plugin options may be useful for projects that need to connect or extend the tool.
Who it suits
DataCleaner may suit people who need to profile and cleanse data from files or databases, as well as developers who want to embed it or create plugins. Its desktop availability covers Linux, macOS, and Windows.
Plans and prices
Community edition
Open-source desktop toolkit · profiling, cleansing and enrichment · Windows, macOS and Linux downloads
Read 15 Oct 2026 · datacleaner.github.io
DataCleaner community edition
Open source · LGPL
Read 30 Sep 2026 · datacleaner.github.io
On the record
- Analyzers
- Reference documentation lists completeness, character-set, date/time, number, pattern, referential-integrity, uniqueness, value-distribution and machine-learning analyzers.datacleaner.github.io · read 15 Oct 2026
- Cleansing
- Users can build cleansing rules using search and replace, regular expressions, pattern matching, or custom transformations.datacleaner.github.io · read 30 Sep 2026
- Code execution
- Developer documentation explains how to configure, build, execute and retrieve results from DataCleaner jobs through code.datacleaner.github.io · read 15 Oct 2026
- Command line
- The reference manual documents command-line execution, parameterized jobs and runtime configuration overrides.datacleaner.github.io · read 15 Oct 2026
- Company ownership history
- The survey states that DataCleaner was developed by Human Inference, later moved through Neopost and Quadient, and from 2019 was associated with EDM Media Group.frontiersin.org · read 15 Oct 2026
- Data profiling
- Its profiling engine identifies patterns, missing values, character sets and other characteristics of data.datacleaner.github.io · read 15 Oct 2026
- Data sources
- It handles CSV files, Excel spreadsheets, relational databases, and NoSQL databases.datacleaner.github.io · read 30 Sep 2026
- Datastore connectors
- Documentation covers JDBC databases, CSV, fixed-width files, Excel, XML, Elasticsearch, MongoDB and CouchDB datastores.datacleaner.github.io · read 15 Oct 2026
- Data wrangling
- The application supports cleansing workflows using reference data, search-and-replace rules, regular expressions, pattern matching and custom transformations.datacleaner.github.io · read 15 Oct 2026
- Deployment model
- Downloads are supplied as desktop archives for Windows, macOS and Linux, with source tags also available.datacleaner.github.io · read 15 Oct 2026
- Discussion and support
- Community discussion posts are powered by GitHub issues and use the Discussion or Question label.datacleaner.github.io · read 30 Sep 2026
- Documentation depth
- The documentation archive includes reference versions 5.7.0, 5.4.0 and 5.2, covering end-user, configuration, CLI, integration and developer topics.datacleaner.github.io · read 15 Oct 2026
- Ecosystem
- The project describes community driven extensions, integrations, and shared content.datacleaner.github.io · read 30 Sep 2026
- Extensibility
- The developer guide covers extension tutorials, packaging, annotated components, single-JAR extensions and embedding DataCleaner.datacleaner.github.io · read 15 Oct 2026
- File and database inputs
- The official site says it handles CSV, Excel, relational databases and NoSQL databases.datacleaner.github.io · read 15 Oct 2026
- Integrations
- The project advertises Apache Hadoop, Apache Spark, Pentaho Data Integration and Apache MetaModel integrations.datacleaner.github.io · read 15 Oct 2026
- Java compatibility
- The 5.8.1 release announcement says the software runs on Java versions 9 through 17.datacleaner.github.io · read 15 Oct 2026
- Java support
- The release news states DataCleaner 5.8.1 runs on Java versions 9 through 17.datacleaner.github.io · read 30 Sep 2026
