Compare the Top ETL Software that integrates with Dataiku as of September 2025

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

What is ETL Software for Dataiku?

ETL software is used to extract, transform and load data between multiple databases in order to organize and structure it for further analysis. Compare and read user reviews of the best ETL software for Dataiku currently available using the table below. This list is updated regularly.

  • 1
    Snowflake

    Snowflake

    Snowflake

    Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.
    Starting Price: $2 compute/month
  • 2
    Apache Hive

    Apache Hive

    Apache Software Foundation

    The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API.
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