The Feldera Incremental Computation Engine
Functional relational programming for Clojure(Script).
Differential Dataflow & Incremental View Maintenance for JavaScript
Denormalized and aggregated tables for PostgreSQL.
Incremental View Maintenance support for DuckDB
My Masterthesis in Data Engineering and Analytics "Expressing CRDTs with Datalog" at TUM.
OpenIVM Spark Extension
Metadata-driven incremental view maintenance for Iceberg tables on Trino — bucket-aware aggregating MVs, no full rescans
Non-blocking incremental materialized views for PostgreSQL, with real-time delta subscriptions. A PostgreSQL 17 extension in Rust.
Rust-native, Spark-compatible compute engine for the agentic era — batch SQL, streaming and incremental materialized views, from embedded to distributed.
DAFSA-backed Datalog engine in Zig: load facts, compile Datalog to a VM, materialize + serve from mmap snapshots. Docs: https://fixpointlinux.org/datalog-dafsa/
Incremental computation engine for Go with live what-if worlds: fork the graph into N scenarios that pin some inputs and track the rest live, all updated by one stabilization. Data-shaped topology (Bind), per-key diff collections, O(divergence) scenario cost.
Embeddable Incremental View Maintenance (IVM) engine implementing DBSP-inspired differential dataflow for SQL queries, joins, aggregates, and real-time updates.
Experimental incremental materialized views for SQLite, implemented in Rust.
Feldera — independent third-party profile of a public API surface, by API Evangelist. Feldera is an incremental compute engine for running complex SQL data pipelines in real time. Rather than reprocessing entire datasets, it updates materialized views proportionally to the changes in the input data, delivering low-latency, low-cost results for use
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