We broke the scaling laws of compute

Feldera's award-winning incremental compute engine runs SQL pipelines of any complexity — and keeps compute costs and latencies flat, even if you process 1,000x more data

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Trusted by leading engineering teams

Portrait of Kristoffer Føllesdal — Kristoffer Føllesdal
Solutions Architect Eviny Fornybar

Portrait of Bruno Rucy — Bruno Rucy
Solana Vibe Station, Lucidarium

Portrait of Jim Dowling — Jim Dowling
Co-Founder & CEO Hopsworks

Portrait of Graham Neray — Graham Neray
CEO & Co-Founder OSO

See how it works

Why is Feldera so fast?

Because we don't recompute. Ever.

We broke a 50-year barrier in database research. Using award-winning math, we can maintain *any* SQL query over changing data. Instead of reprocessing your entire data warehouse every time something updates, Feldera computes only what changes. Queries that took hours now update in milliseconds. This means your teams can bring their existing SQL without rewriting a single query, run historical backfills and real-time data in a single pipeline, and ship complex production use cases in hours.

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Built to enable modern products

What teams actually build when data updates in milliseconds instead of hours

Knowledge graphs for AI

AI products need structured context that's always current, not hours stale. Feldera maintains your knowledge graph and views over it incrementally—when underlying data changes, only the affected nodes and edges update, in milliseconds. Your AI always queries a graph that reflects reality right now.
Lakehouse -> Feldera -> AI-ready knowledge graph

Real-time data pipelines

Most data pipelines recompute everything on every run, even though less than 0.1% of the data changed. Feldera runs your existing SQL incrementally, with no orchestration code and no scheduled batch jobs. What used to take a 70-node cluster now runs on 2 nodes.
Sensor Telemetry -> Feldera -> Fresh dashboards

Fraud detection

Batch-based detection means fraud can go unnoticed for hours. Feldera continuously correlates signals across live and historical data in a single SQL pipeline. Rolling windows, enrichment, and complex joins all running incrementally. Catch fraud before the transaction clears, not after the damage is done.

Clickstream and event analytics

User clicks, transactions, sessions create unbounded streams that never stop growing. Most streaming engines choke on the SQL complexity these workloads demand. Feldera handles sliding windows, sessionization, and complex aggregations over infinite streams using finite resources, with correctness guarantees that no system can match at this speed.

User segmentation

Marketing teams need segments that update the moment a user does something, not whenever the next batch job runs. Feldera replaces hand-coded evaluation engines with declarative SQL views that update incrementally on every event. One pipeline handles both historical backfill and live streaming, with perfect multi-tenant isolation.

Fine-grained authorization

Every authorization request means an expensive traversal of a massive, constantly changing object graph. Feldera precomputes every authorization decision and incrementally updates only what's affected when the graph changes, in milliseconds, using complex recursive SQL that no other engine can evaluate incrementally.
App -> Feldera -> Authorization index in Postgres

Bring your existing SQL as-is

SQL you already run in batch, at speeds you've never seen

Your first pipeline

Ready to eliminate wasteful recomputation?

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