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Enterprise Layer Intelligence
Categories/Data Platform & Integration/Feldera
Feldera

Feldera

Founded 2023

Keep complex SQL query results up to date continuously as your data changes

You can use Feldera to keep continuous SQL queries updated in real time without recomputing entire datasets from scratch. The engine uses incremental view maintenance to calculate only the changes whenever underlying tables update, delivering fresh query outputs in milliseconds. You can run complex data pipelines with hundreds of joins, aggregations, and recursive queries using standard SQL. It connects directly with your data lakehouse to replace heavy batch jobs, cut down compute costs, and support live use cases like fraud detection and access control.

What Feldera does

Write standard SQL queries to define incremental materialized viewsConnect incoming data streams to lakehouse tablesEvaluate recursive SQL queries across dynamic permission graphsCompute rolling aggregations for live transaction monitoringTrack data state transitions without writing custom ETL pipelinesTest pipeline performance using the interactive sandbox environmentCalculates view updates by evaluating only data changes instead of full tablesMaintains complex SQL views including hundreds of joins and aggregationsProcesses recursive queries for graph data and authorization modelsUpdates analytical views with sub-second data freshnessOperates directly on lakehouse data formats without batch processingRuns standard SQL queries without requiring custom streaming codeProvides mathematical correctness guarantees via the DBSP engine

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Feldera, incremental view maintenance, IVM, SQL engine, DBSP, stream processing, real-time data, data lakehouse, data pipelines, batch processing replacement, recursive SQL, fraud detection pipelines, real-time analytics, materialized views, lakehouse views