Compare the Top Data Pipeline Software that integrates with OpenAI as of November 2025

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

What is Data Pipeline Software for OpenAI?

Data pipeline software helps businesses automate the movement, transformation, and storage of data from various sources to destinations such as data warehouses, lakes, or analytic platforms. These platforms provide tools for extracting data from multiple sources, processing it in real-time or batch, and loading it into target systems for analysis or reporting (ETL: Extract, Transform, Load). Data pipeline software often includes features for data monitoring, error handling, scheduling, and integration with other software tools, making it easier for organizations to ensure data consistency, accuracy, and flow. By using this software, businesses can streamline data workflows, improve decision-making, and ensure that data is readily available for analysis. Compare and read user reviews of the best Data Pipeline software for OpenAI currently available using the table below. This list is updated regularly.

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    Gathr.ai

    Gathr.ai

    Gathr.ai

    Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500
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    Starting Price: $0.25/credit
  • 2
    GlassFlow

    GlassFlow

    GlassFlow

    GlassFlow is a serverless, event-driven data pipeline platform designed for Python developers. It enables users to build real-time data pipelines without the need for complex infrastructure like Kafka or Flink. By writing Python functions, developers can define data transformations, and GlassFlow manages the underlying infrastructure, offering auto-scaling, low latency, and optimal data retention. The platform supports integration with various data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, through its Python SDK and managed connectors. GlassFlow provides a low-code interface for quick pipeline setup, allowing users to create and deploy pipelines within minutes. It also offers features such as serverless function execution, real-time API connections, and alerting and reprocessing capabilities. The platform is designed to simplify the creation and management of event-driven data pipelines, making it accessible for Python developers.
    Starting Price: $350 per month
  • 3
    Kestra

    Kestra

    Kestra

    Kestra is an open-source, event-driven orchestrator that simplifies data operations and improves collaboration between engineers and business users. By bringing Infrastructure as Code best practices to data pipelines, Kestra allows you to build reliable workflows and manage them with confidence. Thanks to the declarative YAML interface for defining orchestration logic, everyone who benefits from analytics can participate in the data pipeline creation process. The UI automatically adjusts the YAML definition any time you make changes to a workflow from the UI or via an API call. Therefore, the orchestration logic is defined declaratively in code, even if some workflow components are modified in other ways.
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