Compare the Top Data Integration Tools that integrate with Python as of June 2025

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

What are Data Integration Tools for Python?

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 Python currently available using the table below. This list is updated regularly.

  • 1
    Peliqan

    Peliqan

    Peliqan

    Peliqan.io is an all-in-one data platform for business teams, startups, scale-ups and IT service companies - no data engineer needed. Easily connect to databases, data warehouses and SaaS business applications. Explore and combine data in a spreadsheet UI. Business users can combine data from multiple sources, clean the data, make edits in personal copies and apply transformations. Power users can use "SQL on anything" and developers can use low-code to build interactive data apps, implement writebacks and apply machine learning. Key Features: Wide range of connectors: Integrates with over 100+ data sources and applications. Spreadsheet UI and magical SQL: Explore data in a rich spreadsheet UI. Use Magical SQL to combine and transform data. Use your favorite BI tool such as Microsoft Power BI or Metabase. Data Activation: Create data apps in minutes. Implement data alerts, distribute custom reports by email (PDF, Excel) , implement Reverse ETL flows and much more.
    Starting Price: $199
  • 2
    Peaka

    Peaka

    Peaka

    Integrate all your data sources, relational and NoSQL databases, SaaS tools, and APIs. Query them as a single data source immediately. Process data wherever it is. Query, cache, and blend data from different sources. Use webhooks to ingest streaming data from Kafka, Segment, etc., into the Peaka BI Table. Replace nightly one-time batch ingestion with real-time data access. Treat every data source like a relational database. Convert any API to a table, and blend and join it with your other data sources. Use the familiar SQL to run queries in NoSQL databases. Retrieve data from both SQL and NoSQL databases utilizing the same skill set. Query and filter your consolidated data to form new data sets. Expose them with APIs to serve other apps and systems. Do not get bogged down in scripts and logs while setting up your data stack. Eliminate the burden of building, managing, and maintaining ETL pipelines.
    Starting Price: $1 per month
  • 3
    Diffusion

    Diffusion

    DiffusionData

    Diffusion is a pioneer in real-time data streaming and messaging solutions. Founded to solve the real-time systems & application connectivity and data distribution challenges experienced by companies worldwide, the company has an international team of business and technology experts. The company’s flagship offering, the Diffusion data platform, makes it easy to consume, enrich, and deliver data reliably. Quickly capitalize on existing or new data sources. Purpose-built to simplify event-driven, real-time application development, Diffusion enables you to swiftly add new capabilities with minimal development costs. Accommodates any size, format, or velocity of data. Provides a flexible, hierarchical data model to organize incoming event-data in a multi-level topic tree structure. Easily scalable to millions of topics. Facilitates transformation of event data using low-code features of the platform. Enables subscription to event-data at a fine-grained level for hyper-personalization.
    Starting Price: $199 per month
  • 4
    Algoreus

    Algoreus

    Turium AI

    All your data needs are delivered in one powerful platform. From data ingestion/integration, transformation, and storage to knowledge catalog, graph networks, data analytics, governance, monitoring, and, sharing. ​ An AI/ML platform that lets enterprises, train, test, troubleshoot, deploy, and govern models at scale to boost productivity while maintaining model performance in production with confidence. A dedicated solution for training models with minimal effort through AutoML or training your case-specific models from scratch with CustomML. Giving you the power to connect essential logic from ML with data. An integrated exploration of possible actions.​ Integration with your protocols and authorization models​. Propagation by default; extreme configurability at your service​. Leverage internal lineage system, for alerting and impact analysis​. Interwoven with the security paradigm; provides immutable tracking​.
  • 5
    Timbr.ai

    Timbr.ai

    Timbr.ai

    The smart semantic layer integrates data with business meaning and relationships, unifies metrics, and accelerates the delivery of data products with 90% shorter SQL queries. Easily model data using business terms to give it common meaning and align business metrics. Define semantic relationships that substitute JOINs so queries become much simpler. Use hierarchies and classifications to better understand data. Automatically map data to the semantic model. Join multiple data sources with a powerful distributed SQL engine to query data at scale. Consume data as a connected semantic graph. Boost performance and save compute costs with an intelligent cache engine and materialized views. Benefit from advanced query optimizations. Connect to most clouds, datalakes, data warehouses, databases, and any file format. Timbr empowers you to work with your data sources seamlessly. When a query is run, Timbr optimizes the query and pushes it down to the backend.
  • 6
    Simba

    Simba

    insightsoftware

    Common dashboards, reporting, and ETL tools often lack connectivity to certain data sources, creating integration challenges for users. Simba offers ready-to-use, standards-based drivers that ensure compatibility, simplifying the connectivity process. Companies that provide data to customers struggle to offer headache-free, easy data connectivity to their users. Simba’s SDK allows developers to build custom, standards-based drivers, making connectivity more friendly than CSV export or API-based access. Unique backend requirements, such as specific implementation needs dictated by specific applications or internal processes, can complicate connectivity. Using Simba’s SDK or managed services enables the creation of drivers tailored to meet these requirements. Simba provides comprehensive ODBC/JDBC extensibility for a wide range of applications and data tools. Simba Drivers plug into these tools to enhance their offerings, enabling additional connectivity to data sources.
  • 7
    TROCCO

    TROCCO

    primeNumber Inc

    TROCCO is a fully managed modern data platform that enables users to integrate, transform, orchestrate, and manage their data from a single interface. It supports a wide range of connectors, including advertising platforms like Google Ads and Facebook Ads, cloud services such as AWS Cost Explorer and Google Analytics 4, various databases like MySQL and PostgreSQL, and data warehouses including Amazon Redshift and Google BigQuery. The platform offers features like Managed ETL, which allows for bulk importing of data sources and centralized ETL configuration management, eliminating the need to manually create ETL configurations individually. Additionally, TROCCO provides a data catalog that automatically retrieves metadata from data analysis infrastructure, generating a comprehensive catalog to promote data utilization. Users can also define workflows to create a series of tasks, setting the order and combination to streamline data processing.
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