- Adaptive Scaling
Implement adaptive scaling to automatically adjust materialized view parallelism based on the number of CPU cores in the cluster.
- Improvements on the Existing External Sinks
Optimize performance and improve stability of supported external sinks like Doris, Clickhouse, and Elasticsearch. We’ll also expand supported encoding formats for Kafka sink, including Protobuf, Avro, and the support for Schema Registry.
- Iceberg Sink V2
We recently introduced a native integration with Iceberg, which is no longer based on the official Java library. It’s fully rewritten by Rust for performance and stability. We plan to stabilize it in the next few months.
- Enhanced Observability
Expand system tables and add metrics for stateful operators to provide greater visibility into system health and performance.
- Improved Open-source Web UI
Enhance RisingWave's open-source web UI with additional system information and monitoring capabilities.
- Sink into table
Users may want to dynamically union the results of multiple views into a single table. For example, a view may correspond to an department in a company while there can be new departments once in a while. With this feature, users can seamlessly merging data from new views as they are added.
- CDC Connection Sharing
RisingWave currently creates one CDC connection per table. Each connection will individually consume the replication logs, which consists of transactions not only to the source table, but also other tables in the same database. Therefore, multiple connections will lead to the duplicate consumption and a heavy load on the upstream database. Shared CDC connections can thus reduce the load and improve the stability of CDC.
- Recoverable
CREATE MATERIALIZED VIEW
Persist materialized view progress to allow recovering from failures without losing work already completed.
- CDC Transaction Atomicity
CDC transactions in RisingWave currently applies by events, which may contain only partial content in a transaction. With the new feature, RisingWave will buffer all CDC events within a transaction until it can be fully applied atomically.
- Parallel CDC Snapshot Loading
Introduce parallelism during CDC snapshot loading to improve user experience for large upstream tables.