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Fluss Roadmap

This roadmap provides a high-level summary of ongoing efforts in the Fluss community. Fluss is positioned as the Streaming Storage for Real-Time Analytics and AI.

For detailed tracking, see the Fluss 2026 Roadmap.

Real-Time AI and ML​

  • Real-Time Feature Store with aggregation merge engines, schema evolution, and point-in-time correctness.
  • Multimodal Streaming Data support for rows, columns, vectors, variant, and images.
  • High-performance Rust/Python SDK integrating PyTorch, Ray, Pandas, and PyArrow.

Real-Time Lakehouse​

  • Iceberg V3, Hudi, and Delta Lake integration
  • In-Place Lakehouse: Define Fluss tables on existing Lake tables
  • Native Union Read for Spark, Trino, and StarRocks
  • Deletion Vectors to accelerate updates and deletes

Streaming Analytics​

  • Global Secondary Index for non-primary key lookups
  • Delta Join with multi-stream and left/right/full join support
  • Cost-Based Optimizer in Flink SQL with Fluss table statistics
  • Full Spark Engine support with Structured Streaming integration

Storage Engine​

  • Columnar Streaming with Filter and Aggregation Pushdown
  • Full Schema Evolution with table renaming and column defaults

Cloud-Native Architecture​

  • ZooKeeper Removal for simpler deployment
  • Zero Disks: Direct S3 writes for elastic, diskless storage

Connectivity and Ingestion​

  • Log agent integration
  • Client SDKs: Rust, C++, Python

Operational Excellence​

  • Automated cluster rebalancing and bucket rescaling
  • Coordinator HA with multi-AZ and cross-cluster geo-replication

Security​

  • (m)TLS for intra-cluster, ZooKeeper, and external clients

This roadmap is subject to change based on community feedback and evolving requirements.