Best Data Integration Tools for Jupyter Notebook

Compare the Top Data Integration Tools that integrate with Jupyter Notebook as of October 2025

This a list of Data Integration tools that integrate with Jupyter Notebook. Use the filters on the left to add additional filters for products that have integrations with Jupyter Notebook. View the products that work with Jupyter Notebook in the table below.

What are Data Integration Tools for Jupyter Notebook?

Data integration tools help organizations combine data from multiple sources into a unified, coherent system for analysis and decision-making. These tools streamline the process of gathering, transforming, and loading data (ETL) from various databases, applications, and cloud services, ensuring consistent data across platforms. They provide features like data cleansing, mapping, and real-time synchronization, ensuring data accuracy and reliability. With automated workflows and connectors, data integration tools reduce manual effort and eliminate data silos, improving operational efficiency. Ultimately, they enable businesses to make better, data-driven decisions by providing a comprehensive view of their information landscape. Compare and read user reviews of the best Data Integration tools for Jupyter Notebook currently available using the table below. This list is updated regularly.

  • 1
    Datameer

    Datameer

    Datameer

    Datameer revolutionizes data transformation with a low-code approach, trusted by top global enterprises. Craft, transform, and publish data seamlessly with no code and SQL, simplifying complex data engineering tasks. Empower your data teams to make informed decisions confidently while saving costs and ensuring responsible self-service analytics. Speed up your analytics workflow by transforming datasets to answer ad-hoc questions and support operational dashboards. Empower everyone on your team with our SQL or Drag-and-Drop to transform your data in an intuitive and collaborative workspace. And best of all, everything happens in Snowflake. Datameer is designed and optimized for Snowflake to reduce data movement and increase platform adoption. Some of the problems Datameer solves: - Analytics is not accessible - Drowning in backlog - Long development
  • 2
    Tengu

    Tengu

    Tengu

    TENGU is a DataOps Orchestration Platform that works as a central workspace for data profiles of all levels. It provides data integration, extraction, transformation, loading all within it’s graph view UI in which you can intuitively monitor your data environment. By using the platform, business, analytics & data teams need fewer meetings and service tickets to collect data, and can start right away with the data relevant to furthering the company. The Platform offers a unique graph view in which every element is automatically generated with all available info based on metadata. While allowing you to perform all necessary actions from the same workspace. Enhance collaboration and efficiency, with the ability to quickly add and share comments, documentation, tags, groups. The platform enables anyone to get straight to the data with self-service. Thanks to the many automations and low to no-code functionalities and built-in assistant.
  • 3
    OpenHexa

    OpenHexa

    Bluesquare

    Understanding health issues often requires combining complex and heterogeneous data sources, even in the context of single-country interventions. Data can come from HMIS platforms such as DHIS2, from individual tracking systems, from custom software built to address specific issues, or from various Excel reports provided by health experts. Having such diverse data in disconnected silos is often the biggest obstacle to an efficient exploration and analysis process. It also makes collaboration difficult, and many data analysts working on health data end up developing ad-hoc scripts and visualisations on their own laptops and communicating their results in scattered publications from which it is hard to get unified insights. To address this issue, Bluesquare has built OpenHexa, a cloud-based data integration platform consisting of three components, extraction, analysis & visualization. This platform is mostly based on mature open-source technologies.
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