The Incremental Compute Engine for AI, ML and data teams
Feldera is a fast query engine with the unmatched ability to evaluate arbitrary SQL programs incrementally, over any number of live and historical data sources. Process millions of events per second and scale to larger than memory datasets, even on your laptop.
Use cases
Real-time Feature Engineering
Get perfect offline-online parity, zero feature skew, instant feature freshness and process millions of events per second. Ship new features in days (not months), by reusing the same complex SQL to do feature engineering in both offline (batch) or online (real-time) settings.
Use cases
Threat, identity and fraud platforms
Run thousands of complex queries to incrementally enrich, correlate and aggregate over multiple signals in real-time to stop bad actors. Whether ML-based or rule-based, compute with perfect offline-online parity at millions of events per second.
Use cases
Operational analytics
Incrementally compute over unbounded streams of live and historical data generated from your cloud and edge. Integrate-with and alleviate pressure from your lakehouse or warehouse.
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.
Alex Bewley
Director, Engineering - VMwareIncremental 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.
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
Evaluate complex SQL over both batch and streaming data sources, seamlessly handling inserts, updates and deletes.
Documentation
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
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.
DocumentationFeldera pipelines can connect to multiple heterogeneous data sources and destinations.
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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