Batch jobs waste 99.9% of their time reprocessing unchanged data

Feldera’s award-winning incremental compute platform erases that waste with instant incremental updates. Whether processing monster SQL pipelines with hundreds of joins or recursive graph analytics, process millions of changes per second even on a laptop.

Use cases

From batch to incremental analytics

Feldera users take monster SQL jobs from their Databricks or Snowflake instances and run them fully incrementally in Feldera. We’re talking pipelines with deeply nested views, *hundreds* of joins, unions, distincts and aggregates updating at sub-second speeds.

    Use cases

    Recursive queries and graph computing

    Feldera users run sophisticated recursive graph queries to power real-time security and observability. What once took multi-year ad-hoc engineering are now simple Feldera pipelines, processing millions of graph updates per second per node.

      Use cases

      Threat, identity and fraud platforms

      Feldera users incrementally enrich, correlate, and aggregate multiple signals in real time to stop bad actors. They achieve perfect offline-online parity, whether ML- or rule-based, processing millions of events per second.

        VMware Skyline used the Feldera team's technology to digest terabytes of streaming data and execute thousands of complex rules instantaneously. We reduced our end-to-end recommendation notification time from twenty-four hours to minutes. The engine is ridiculously fast and was never a compute bottleneck for the three years it has been in production.

        Portrait of Alex Bewley

        Alex Bewley

        Director, Engineering - VMware

        Incremental computation has never been this easy

        Go from painful data-engineering and ad-hoc solutions to “Just Writing SQL”. Define tables and deeply nested layers of views. When inputs receive changes (inserts, updates or deletes), all views are incrementally updated in an instant. Try it right away.

        Incremental computation has never been this easy

        The state-of-the-art in Incremental Computation

        Powered by our open-source compute engine, written from scratch in Rust.

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        A unified query engine for offline and online compute, no compromises

        A unified query engine for offline and online compute, no compromises

        Evaluate complex SQL over both batch and streaming data sources, seamlessly handling inserts, updates and deletes.

        Documentation
        Unmatched performance

        Unmatched performance

        Our users routinely see millions of events per second on a single machine, out-of-the-box, even for sophisticated pipelines with complex views computed over many streams.

        Documentation
        Fully automatic incremental compute, powered by award-winning research

        Fully automatic incremental compute, powered by award-winning research

        We’ll take care of the incremental algorithms, strong consistency, spilling to fast storage, failure recovery and keeping memory stable even when computing over infinite streams.

        Documentation

        Feldera pipelines can connect to multiple heterogeneous data sources and destinations.

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        The Feldera Community

        Join our growing community of users, engineers and enthusiasts to discuss incremental computation, databases, streaming, Rust, and all things data.

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