Compare the Top Data Pipeline Software that integrates with Fivetran as of May 2026

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

What is Data Pipeline Software for Fivetran?

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

  • 1
    Dagster

    Dagster

    Dagster Labs

    Dagster is a next-generation orchestration platform for the development, production, and observation of data assets. Unlike other data orchestration solutions, Dagster provides you with an end-to-end development lifecycle. Dagster gives you control over your disparate data tools and empowers you to build, test, deploy, run, and iterate on your data pipelines. It makes you and your data teams more productive, your operations more robust, and puts you in complete control of your data processes as you scale. Dagster brings a declarative approach to the engineering of data pipelines. Your team defines the data assets required, quickly assessing their status and resolving any discrepancies. An assets-based model is clearer than a tasks-based one and becomes a unifying abstraction across the whole workflow.
    Starting Price: $0
  • 2
    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
  • 3
    DataOps.live

    DataOps.live

    DataOps.live

    DataOps.live, the Data Products company, delivers productivity and governance breakthroughs for data developers and teams through environment automation, pipeline orchestration, continuous testing and unified observability. We bring agile DevOps automation and a powerful unified cloud Developer Experience (DX) ​to modern cloud data platforms like Snowflake.​ DataOps.live, a global cloud-native company, is used by Global 2000 enterprises including Roche Diagnostics and OneWeb to deliver 1000s of Data Product releases per month with the speed and governance the business demands.
  • 4
    Orchestra

    Orchestra

    Orchestra

    Orchestra is a Unified Control Plane for Data and AI Operations, designed to help data teams build, deploy, and monitor workflows with ease. It offers a declarative framework that combines code and GUI, allowing users to implement workflows 10x faster and reduce maintenance time by 50%. With real-time metadata aggregation, Orchestra provides full-stack data observability, enabling proactive alerting and rapid recovery from pipeline failures. It integrates seamlessly with tools like dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and more, ensuring compatibility with existing data stacks. Orchestra's modular architecture supports AWS, Azure, and GCP, making it a versatile solution for enterprises and scale-ups aiming to streamline their data operations and build trust in their AI initiatives.
  • 5
    Astro by Astronomer
    For data teams looking to increase the availability of trusted data, Astronomer provides Astro, a modern data orchestration platform, powered by Apache Airflow, that enables the entire data team to build, run, and observe data pipelines-as-code. Astronomer is the commercial developer of Airflow, the de facto standard for expressing data flows as code, used by hundreds of thousands of teams across the world.
  • 6
    Databricks

    Databricks

    Databricks

    The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
  • 7
    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.
  • 8
    Pantomath

    Pantomath

    Pantomath

    Organizations continuously strive to be more data-driven, building dashboards, analytics, and data pipelines across the modern data stack. Unfortunately, most organizations struggle with data reliability issues leading to poor business decisions and lack of trust in data as an organization, directly impacting their bottom line. Resolving complex data issues is a manual and time-consuming process involving multiple teams all relying on tribal knowledge to manually reverse engineer complex data pipelines across different platforms to identify root-cause and understand the impact. Pantomath is a data pipeline observability and traceability platform for automating data operations. It continuously monitors datasets and jobs across the enterprise data ecosystem providing context to complex data pipelines by creating automated cross-platform technical pipeline lineage.
  • 9
    QuickLaunch Analytics

    QuickLaunch Analytics

    QuickLaunch Analytics

    QuickLaunch Analytics is an enterprise data analytics platform that helps organizations turn fragmented data from ERP, CRM, financial, HR and operational systems into a unified, governed analytics ecosystem with faster, business-ready insights; rather than building analytics infrastructure from scratch, it provides a Foundation Pack that includes automated data pipelines, a cloud-native data lakehouse and Power BI semantic models so raw enterprise data can be integrated, cleaned, and governed for analytics, and Application Packs that layer pre-built, application-specific intelligence and production-ready semantic models tailored to systems like JD Edwards, Viewpoint Vista, NetSuite, Salesforce and others to decode complex data structures into business-friendly metrics and dashboards; the platform accelerates time-to-insight from months/years to weeks with standardized metrics and reports, supports cross-application analysis and self-service BI, and uses modern technologies.
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