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DataCleaner

Free#11 of 26 in Data Preparation SoftwareData Cleansing Software

DataCleaner: A free visual toolkit for building data-quality workflows across files and databases. Ranked #11 of 26 in Data Preparation Software by our editors (7.4/10); pricing: Free plan; best for free visual data-quality workflows.

7.4/10Editor score
DataCleaner7.4 Visit DataCleaner

At a glance

  • Editor score
    7.4 / 10
  • Pricing
    Free plan
  • Best for
    Free visual data-quality workflows
  • Free plan
    Yes
  • Paid from
    Free
  • Deployment
    Desktop
  • Facts checked
    20 Sep 2026
DataCleaner screenshot
  • Where it wins

    • Profiles patterns, missing values, character sets, and other data characteristics
    • Builds visual job graphs with analyzers, transformers, and filters
    • Supports CSV, Excel, relational databases, and NoSQL datastores
  • Where it doesn't

    • The project is maintained but not actively developed
    • Fewer listed integrations than commercial category leaders
    • Desktop deployment may not suit teams seeking a broader hosted platform

Our verdict on DataCleaner

DataCleaner is an open-source data quality toolkit for profiling, transforming, cleansing, and enriching data. Its desktop application lets teams create visual job graphs with analyzers, transformers, and filters. The product is suited to data professionals who need repeatable quality workflows across CSV files, Excel spreadsheets, relational databases, and NoSQL datastores, while still retaining command-line execution and code-based job invocation.

The main strength is the depth of its data-quality workflow. Data profiling covers patterns, missing values, character sets, and other data characteristics, while quality analyzers address completeness, uniqueness, referential integrity, and value distribution. Transformation and cleansing rules can use scripts, lookups, and pattern matching. Processed data can be written to CSV, Excel, staging tables, or database tables, giving the toolkit a practical path from inspection to output. Scheduled runs, command-line execution, APIs for embedding, and Hadoop and Spark interfaces also extend it beyond a purely interactive desktop utility.

DataCleaner has no paid cost and runs on Windows, macOS, and Linux. Its ecosystem includes Apache Hadoop, Apache Spark, Pentaho Data Integration, and Apache MetaModel, although the listed integration set is narrower than those of commercial leaders. The project is maintained but not actively developed, and Community Edition 5.9.0 is listed as the latest release. Choose DataCleaner if free, open-source visual workflows and broad file and database support matter more than a large commercial integration ecosystem. Teams seeking a more actively developed product or a broader hosted platform should consider an alternative.

Your product? Our editors can test DataCleaner in depth and publish a review, labelled as paid · from $149/mo →

DataCleaner pricing

Plans Free planFree Free to use — no paid tier required for the core job.
See plans on datacleaner.github.io

DataCleaner fact sheet

Free planYes
Paid fromFree
Data profilingYes
Visual workflowsYes
DeploymentDesktop
Scheduled runsYes
Source connectorsNot verified
Row limitNot verified
DeploymentDesktop
PlatformsWindows, macOS, Linux
SupportCommunity, Docs
Built forSmall business, Mid-market, Enterprise (editorial estimate)
Integrations4 integrations: Apache Hadoop, Apache Spark, Pentaho Data Integration, Apache MetaModel
PricingFree plan
Websitedatacleaner.github.io
Facts checked20 Sep 2026

DataCleaner integrations

DataCleaner lists 4 integrations on its own site.

  • Apache Hadoop
  • Apache Spark
  • Pentaho Data Integration
  • Apache MetaModel

Alternatives to DataCleaner

See all DataCleaner alternatives →

Also Ranked In

DataCleaner is ranked in 2 of our directories.

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Featured on iTechGuides

Featured on iTechGuides — DataCleaner 7.4/10

DataCleaner is listed in our Data Preparation Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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