RisingWave
Relational databases
Big data processing and distribution systems
Event stream processing software
Big data integration platforms
ETL tools
iPaaS software
Stream analytics software
Data extraction tools
Database software
Big data software
Data integration tools
Cloud data integration software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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What is RisingWave
RisingWave is a distributed SQL engine for processing and analyzing streaming data with low-latency, incremental computation. It targets data engineering and analytics teams that need continuous materialized views, real-time dashboards, and streaming ETL into analytical stores. The system provides PostgreSQL-compatible SQL for defining streams and materialized views and typically integrates with message brokers and object storage for ingestion and persistence. It is commonly deployed in cloud or containerized environments to support scalable stream processing using familiar relational concepts.
SQL-based streaming semantics
RisingWave uses SQL (with PostgreSQL-style compatibility) to define streaming sources, transformations, and materialized views. This lowers the barrier for teams that already use relational databases and SQL-based analytics tools. It supports incremental updates so downstream queries can read continuously maintained results rather than recomputing full aggregates. This approach fits use cases such as real-time metrics, anomaly detection features, and continuously updated dimensional aggregates.
Continuous materialized views
The product centers on maintaining materialized views over streams, which simplifies building real-time serving tables for applications and BI. Teams can model pipelines as view definitions and let the engine manage incremental maintenance. This can reduce custom code compared with building and operating separate streaming jobs plus batch backfills. It also supports multiple concurrent queries over the same ingested streams, which can improve reuse across teams.
Distributed, cloud-friendly deployment
RisingWave is designed as a distributed system and is commonly deployed via containers/Kubernetes, aligning with modern cloud operations. It separates ingestion, compute, and storage concerns in a way that supports horizontal scaling for higher throughput. This makes it suitable when a single-node relational database is insufficient for stream workloads. It also fits architectures that need to integrate streaming processing with cloud object storage and external sinks.
Not a general OLTP database
Although it exposes SQL and relational concepts, RisingWave is primarily a stream processing and stream analytics engine rather than a full-featured transactional database. Workloads that require strict OLTP semantics, complex transactional workflows, or broad ecosystem support for stored procedures and extensions may be a poor fit. Organizations may still need a separate operational database for application transactions. This can add architectural complexity when teams expect one system to cover both streaming and OLTP.
Operational complexity at scale
Running a distributed streaming system typically requires careful capacity planning, monitoring, and incident response for backpressure, state growth, and recovery behavior. Teams without experience operating stream processors may face a learning curve in production. Achieving predictable latency can depend on tuning resources, checkpointing/state settings, and upstream broker configurations. This can be more involved than operating managed relational database services.
Connector and ecosystem gaps
Integration breadth varies by connector maturity and supported sinks/sources, and some environments may require custom integration work. Compared with long-established database platforms and managed services, enterprise features and third-party tooling support can be less comprehensive depending on the deployment model. Teams may need to validate compatibility with their preferred orchestration, governance, and catalog tools. This is especially relevant for organizations standardizing on a single vendor’s integrated data platform.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Basic | From $0.227 / RWU / hour (pay-as-you-go; after 7-day free trial) | Fully hosted (AWS, GCP, Azure); Up to 64 cores; Core features; Standard support; Pay-as-you-go. 7-day free trial available. |
| Pro | Pay-as-you-go or Annual contract (contact sales for pricing) | Fully hosted or BYOC; No core limits; Premium features; Premium support & SLA. |
| Self-managed | Annual contract / Request license (contact sales) | On-prem / Kubernetes; No core limits; Premium features; Premium support & SLA + quarterly success review. |
Additional usage-based charges (documented examples on official site):
- Compute: base example rate $0.227 per RWU-hour (1 RWU = max(vCPU, memory_GB/4)).
- Storage: example $0.0299 per GB-month.
- Network (AWS US/EU example): public ingress $0.07/GB; public egress $0.17/GB. (Rates vary by cloud provider and region; see vendor docs for full table.)
Seller details
RisingWave Labs
San Francisco, CA, USA
2021
Private
https://www.risingwave.com/
https://x.com/risingwavelabs
https://www.linkedin.com/company/risingwave-labs/
