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Apache Fluss

10 articles · Page 1 of 1
Lakehouse Research Base
Lakehouse Research Base
Sep 10, 2026 · Databases

Apache Fluss Virtual Tables: $changelog vs $binlog for Queryable Change Streams

This article deep-dives into Apache Fluss virtual tables, explaining how $changelog and $binlog suffixes expose change logs as read-only queryable tables, detailing their schemas, use cases, differences between PrimaryKey and Log tables, startup modes, limitations, and the design philosophy enabling native CDC consumption via SQL without external tools.

Apache FlussBinlogCDC
0 likes · 9 min read
Apache Fluss Virtual Tables: $changelog vs $binlog for Queryable Change Streams
Lakehouse Research Base
Lakehouse Research Base
Aug 24, 2026 · Big Data

Apache Fluss: Four Merge Engines Explained for Real-Time Analytics

This article systematically analyzes Apache Fluss's four merge engines—Default (LastRow), FirstRow, Versioned, and Aggregation—covering core principles, supported operations, behavior examples, applicable scenarios, and a production selection guide for real-time data warehousing.

AggregationApache FlussFirstRow
0 likes · 14 min read
Apache Fluss: Four Merge Engines Explained for Real-Time Analytics
Lakehouse Research Base
Lakehouse Research Base
Aug 23, 2026 · Big Data

Apache Fluss Dual-Table Model: LogTable and PrimaryKeyTable Explained

This article details Apache Fluss's dual-table model where LogTable handles high-throughput append-only streaming with columnar storage while PrimaryKeyTable supports real-time updates, partial merges, and CDC changelogs via integrated RocksDB state storage, sharing unified tiering and lakehouse sinking.

Apache FlussCDCLakehouse
0 likes · 19 min read
Apache Fluss Dual-Table Model: LogTable and PrimaryKeyTable Explained
Lakehouse Research Base
Lakehouse Research Base
Aug 22, 2026 · Big Data

Apache Fluss: Dual Engines & Tiered Storage Power Real-Time Lakehouse

This article deep-dives into Apache Fluss architecture, detailing its Master-Worker design, dual LogStore and KvStore engines, tablet-based sharding, tiered hot/cold storage on remote object stores, and Flink-centric client integration, explaining how these components unify streaming and lakehouse workloads.

Apache FlussFlink connectorKvStore
0 likes · 14 min read
Apache Fluss: Dual Engines & Tiered Storage Power Real-Time Lakehouse
Lakehouse Research Base
Lakehouse Research Base
Aug 12, 2026 · Big Data

Apache Fluss Graduates to TLP: Lakestream Unifies Streaming & Lakehouse

Apache Fluss graduates to a top-level project, introducing the Lakestream architecture that unifies real-time streaming and historical lakehouse storage through tiered hot/cold storage, unified metadata, and Union Read, eliminating Lambda architecture complexity and enabling sub-second analytics on a single logical table.

Apache FlussFlinkLakestream
0 likes · 15 min read
Apache Fluss Graduates to TLP: Lakestream Unifies Streaming & Lakehouse
DataFunSummit
DataFunSummit
Aug 7, 2026 · Big Data

Apache Fluss Graduates to Top‑Level Project, Launching Agentic Lake’s Full Real‑Time Era

In July 2024 Apache Fluss received unanimous approval from the Apache Incubator IPMC and ASF board, graduating to a Top‑Level Project; the article details its community growth, core Lakestream architecture, real‑time streaming storage capabilities, adoption by major enterprises, and how it enables AI agents with fresh, unified data for real‑time decisions.

AI AgentApache FlussLakehouse
0 likes · 14 min read
Apache Fluss Graduates to Top‑Level Project, Launching Agentic Lake’s Full Real‑Time Era
DataFunTalk
DataFunTalk
Jun 29, 2026 · Big Data

How Agentic Streaming Is Redefining Real‑Time AI at Flink Forward Asia 2026

The Flink Forward Asia 2026 conference in Shenzhen showcased Apache Flink's evolution to Agentic Streaming for AI, introduced the multimodal Agentic Lake built on Apache Paimon 2.0, announced Fluss 1.0 as a real‑time context layer, and highlighted performance gains over competing stacks such as Ray and Daft.

Agentic StreamingApache FlinkApache Fluss
0 likes · 13 min read
How Agentic Streaming Is Redefining Real‑Time AI at Flink Forward Asia 2026
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jun 27, 2026 · Industry Insights

Key Takeaways from Flink Forward Asia 2026: Agentic Streaming and AI‑Native Real‑Time Data

The Flink Forward Asia 2026 conference in Shenzhen gathered leading experts to discuss the evolution of Apache Flink toward agentic streaming, multimodal data processing, and AI‑native real‑time platforms, highlighting insights from Alibaba Cloud, NVIDIA, and independent researchers on the future of AI‑driven data pipelines.

AIAgentic StreamingApache Flink
0 likes · 5 min read
Key Takeaways from Flink Forward Asia 2026: Agentic Streaming and AI‑Native Real‑Time Data
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jun 26, 2026 · Big Data

Flink Forward Asia 2026 Launches in Shenzhen: Agentic Streaming for AI Opens a New Real-Time Intelligence Era

The Flink Forward Asia 2026 conference in Shenzhen announced the evolution of Apache Flink toward Agentic Streaming for AI, unveiled multimodal data lake projects like Apache Paimon 2.0 and Fluss, highlighted performance gains over competing stacks, and showcased collaborations with NVIDIA to accelerate real‑time AI workloads.

Agentic StreamingApache FlinkApache Fluss
0 likes · 13 min read
Flink Forward Asia 2026 Launches in Shenzhen: Agentic Streaming for AI Opens a New Real-Time Intelligence Era