{"slug":"risingwave","name":"RisingWave","domain":null,"verdict":"As of 2026-08-10, ChatGPT, Claude, Gemini, Grok collectively rank RisingWave #2 of 8 for streaming etl tools for real-time analytics. Source: https://modelsagree.com/product/risingwave (modelsagree.com, CC BY 4.0).","best_rank":2,"categories":1,"entries":[{"slug":"best-streaming-etl-tools-for-real-time-analytics","title":"Best streaming ETL tools for real-time analytics","rank":2,"of":8,"score":15,"appearances":4,"modelRanks":{"ChatGPT":2,"Claude":2,"Gemini":4,"Grok":1},"reason":"Delivers highest practical value for typical practitioners by unifying native CDC (Postgres/MySQL without mandatory Kafka), SQL streaming transforms with cascading materialized views, object-storage state for elastic scale/cost, and direct Postgres-compatible serving of real-time results in one system; strong Nexmark performance and full Apache 2.0 openness reduce ops and TCO versus multi-component stacks. Assumption: most users prioritize SQL accessibility and end-to-end analytics readiness over low-level custom code.","reasons":[{"model":"Grok","reason":"Delivers highest practical value for typical practitioners by unifying native CDC (Postgres/MySQL without mandatory Kafka), SQL streaming transforms with cascading materialized views, object-storage state for elastic scale/cost, and direct Postgres-compatible serving of real-time results in one system; strong Nexmark performance and full Apache 2.0 openness reduce ops and TCO versus multi-component stacks. Assumption: most users prioritize SQL accessibility and end-to-end analytics readiness over low-level custom code."},{"model":"ChatGPT","reason":"Best value for typical analytics teams wanting sub-second pipelines through PostgreSQL-compatible SQL, incremental materialized views, built-in CDC, direct low-latency serving, and open-source or managed deployment. Near-tied with Flink when custom code is unnecessary."},{"model":"Claude","reason":"Postgres-wire-compatible streaming database with incremental materialized views — you write SQL, it maintains results in real time, giving you 80% of Flink's analytics value at a fraction of the operational cost; open source, decoupled compute/storage, and strong price/performance. Near-tie with Materialize (#3): RisingWave wins on cost/scalability, Materialize on consistency and correctness depth."},{"model":"Gemini","reason":"Distributed PostgreSQL-compatible SQL streaming engine that allows data teams to write real-time ETL pipelines and continuous materialized views using standard SQL, eliminating the need to write complex Flink Java/Scala code."}],"fixes":[{"model":"ChatGPT","fix":"Its ecosystem and support for arbitrary processing logic remain narrower than Flink’s."},{"model":"Claude","fix":"Younger ecosystem and largely single-vendor-driven; less proven for very complex custom logic or edge cases than Flink."},{"model":"Gemini","fix":"Less mature ecosystem for non-SQL event-driven procedural logic and legacy batch connectors compared to established open-source stream frameworks."},{"model":"Grok","fix":"Not for workloads needing MATCHRECOGNIZE CEP or heavy non-SQL custom operators"}],"updated":"2026-08-10","rank_history":{"days":["2026-08-03","2026-08-10"],"ranks":[2,1]},"api":"https://modelsagree.com/api/v1/best/best-streaming-etl-tools-for-real-time-analytics.json"}],"page":"https://modelsagree.com/product/risingwave","check":"https://modelsagree.com/check?q=RisingWave","updated":"2026-08-10T18:18:45.051Z","attribution":"modelsagree.com, CC BY 4.0"}