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DirectoryData & AnalyticsStreaming & Real-Time AnalyticsRisingWave

RisingWave

Open Source

About RisingWave

RisingWave is a PostgreSQL-compatible streaming database that handles real-time ingestion, incremental computation, and serving in a single system. It ingests, transforms, and serves live data to agents and applications. It delivers data to managed Apache Iceberg tables for analytics, powered by Apache DataFusion. The platform continuously ingests from event streams, databases, and data lakes, processes data in real time, and delivers results to agents, applications, and analytics. Teams use it to power AI agent infrastructure, streaming ETL, change data capture pipelines, and industry-specific analytics, all written in standard SQL.

Used for

  • Monitoring event streams to detect anomalies as they occur
  • Building real-time enrichment pipelines that join live events with historical records
  • Processing sensor and device data as it streams in
  • Writing continuously to Apache Iceberg without orchestrators or compactors
  • Serving fresh, consistent data to AI agents with sub-second latency via materialized views

From RisingWave's own website, read 2026-10-24. How we build listings.

How to evaluate Streaming & Real-Time Analytics

This is how the CIOPages Research Team evaluates this category. It is not an assessment of RisingWave. It comes from our Streaming Data & Event Processing buyer guide.

25%
Throughput, Latency & Durability
Sustained throughput and tail latency at your partition count, ordering and exactly-once / at-least-once delivery guarantees, replication and multi-AZ durability, retention limits, and behavior under broker failure and rebalancing
20%
Operating Model & Architecture
Self-managed vs. fully managed vs. serverless vs. bring-your-own-cloud, KRaft (post-ZooKeeper) operations, diskless / object-storage-backed options, autoscaling, partition rebalancing, and upgrade and patching burden on your team
20%
Kafka-API Compatibility & Portability
Fidelity of the Kafka protocol (consumer groups, transactions, compaction), reuse of existing clients, connectors and tooling, lock-in to a single cloud, and the realistic effort to migrate in or out
15%
Stream Processing & Ecosystem
Native or integrated processing (Flink, Kafka Streams, Spark Structured Streaming, ksqlDB), connector catalog (CDC, sinks, sources), schema registry and governance, and direct landing into Iceberg / Delta lakehouse tables
10%
Security, Governance & Compliance
Encryption in transit and at rest, mTLS / SASL / OAuth and RBAC, audit logging, private networking, data residency and BYOC data-boundary control, and SOC 2 / ISO 27001 / GDPR coverage
10%
Cost Model & Economics at Scale
Pricing unit (capacity / throughput / consumption), inter-AZ and egress charges, storage and retention cost, processing billed separately, and how the bill behaves as volume, partitions, and connectors grow

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Quick Facts

risingwave.com Pricing page
CategoryData & Analytics
SubcategoryStreaming & Real-Time Analytics
DeploymentFully hosted, BYOC, On-prem / K8s

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Keep reading

Buyer Guide
Real-Time Analytics Databases
Job 01
Decide where AI goes in the business

The board wants an AI plan, and every function wants to go first.

Job 05
Modernize the estate

AI agents need clean data and systems they can call, and old systems block both.