Best Data Cleansing Software for Apache Spark

Compare the Top Data Cleansing Software that integrates with Apache Spark as of December 2025

This a list of Data Cleansing software that integrates with Apache Spark. Use the filters on the left to add additional filters for products that have integrations with Apache Spark. View the products that work with Apache Spark in the table below.

What is Data Cleansing Software for Apache Spark?

Data cleansing software uses specific algorithms in order to search for anomalies across data sets with the purpose of correcting them. Compare and read user reviews of the best Data Cleansing software for Apache Spark currently available using the table below. This list is updated regularly.

  • 1
    TiMi

    TiMi

    TIMi

    With TIMi, companies can capitalize on their corporate data to develop new ideas and make critical business decisions faster and easier than ever before. The heart of TIMi’s Integrated Platform. TIMi’s ultimate real-time AUTO-ML engine. 3D VR segmentation and visualization. Unlimited self service business Intelligence. TIMi is several orders of magnitude faster than any other solution to do the 2 most important analytical tasks: the handling of datasets (data cleaning, feature engineering, creation of KPIs) and predictive modeling. TIMi is an “ethical solution”: no “lock-in” situation, just excellence. We guarantee you a work in all serenity and without unexpected extra costs. Thanks to an original & unique software infrastructure, TIMi is optimized to offer you the greatest flexibility for the exploration phase and the highest reliability during the production phase. TIMi is the ultimate “playground” that allows your analysts to test the craziest ideas!
  • 2
    matchit

    matchit

    360Science

    The foundation of our matching software, matchit® is designed specifically to deliver results that mirror human-like perception, at scale and without preprocessing. Using Artificial Intelligence, a proprietary phonetic algorithm, lexicons, and a contextual scoring engine, matchit defeats the errors, inconsistencies, and challenges commonly found in contact and business data. Conventional matching solutions require a user to define matching logic, which is a combination of functions and off-the-shelf fuzzy algorithms, used to produce an alphanumeric value. This alphanumeric value, or ‘match key’, forms the basis for comparing two records together and ultimately finding matches. Unlike conventional matching solutions, matchit doesn’t rely on a single comparison between match keys to find a match. Instead, matchit evaluates records contextually, running a variety of comparisons and scoring them individually to grade similarity between all the relevant elements that make up your data.
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