RisingWave vs Materialize: An Honest Comparison (2026)

RisingWave and Materialize are both PostgreSQL-compatible streaming databases that maintain incrementally updated materialized views. The key differences: RisingWave is open source (Apache 2.0), self-hostable, stores state on S3, and supports native CDC and Iceberg sinks. Materialize is cloud-only (SaaS), source-available (BSL), offers strict-serializable consistency, and supports recursive CTEs. Choose RisingWave for flexibility and cost efficiency; choose Materialize when strict consistency is non-negotiable.

Architecture

RisingWave

• Written in: Rust
• State storage: S3 / object storage (disaggregated compute-storage)
• Consistency: Snapshot consistency (configurable checkpoint interval, default 1 second)
• Deployment: Self-hosted (Apache 2.0) + managed cloud
• CDC: Native PostgreSQL and MySQL CDC (no Debezium required)
• Sinks: Kafka, Iceberg, Delta Lake, PostgreSQL, Elasticsearch, and more

Materialize

• Written in: Rust (Timely Dataflow + Differential Dataflow)
• State storage: Managed (Persist layer on S3)
• Consistency: Strict-serializable
• Deployment: Cloud-only (SaaS)
• CDC: Native PostgreSQL CDC, Kafka
• Sinks: Kafka, PostgreSQL, webhook

Feature Comparison

Consistency: The Core Difference

The biggest technical difference is the consistency model.

Materialize provides strict-serializable consistency. Every query sees a globally consistent state — if two events happen in sequence in the source database, materialized views always reflect them in order. CDC transactions are processed atomically, regardless of size.

RisingWave provides snapshot consistency. Queries return results consistent with a specific checkpoint. With a default 1-second checkpoint interval, views are at most 1 second behind. For the vast majority of streaming analytics workloads — dashboards, monitoring, event-driven processing — this is more than sufficient.

When strict consistency matters: Financial calculations where an incorrect intermediate state could trigger wrong actions. Regulatory reporting where audit trails require exact consistency. Multi-table joins over CDC data where transaction boundaries are critical.

When snapshot consistency is fine: Real-time dashboards, monitoring and alerting, recommendation engines, clickstream analytics, IoT data processing, feature engineering for ML — essentially all analytics and operational use cases where 1-second consistency is acceptable.

Deployment and Cost

Self-Hosting

RisingWave can be self-hosted on any infrastructure — Kubernetes, bare metal, or cloud VMs. You control the deployment, scaling, and data residency. This matters for:

• Data sovereignty: Keep data in your own infrastructure
• Cost control: No SaaS margins; pay only for compute and S3 storage
• Air-gapped environments: Deploy without internet access
• Custom configurations: Tune for your specific workload

Materialize is only available as a managed SaaS service. You cannot self-host.

Cost Comparison

RisingWave's disaggregated architecture (compute on VMs, state on S3) means you pay:

• Compute: Standard VM pricing
• Storage: S3 pricing (~$0.023/GB/month)
• No SaaS premium

Materialize charges based on compute credits and storage in their managed platform, which typically results in higher total cost — especially at scale.

Ecosystem and Integration

Data Lake Integration

RisingWave has native Iceberg and Delta Lake sink connectors, making it a natural fit for streaming lakehouse architectures. You can simultaneously serve real-time queries via materialized views and sink processed data to Iceberg for historical analytics.

Materialize does not have native Iceberg or Delta Lake sinks. Data lake integration requires routing through Kafka.

UDFs and Extensibility

RisingWave supports user-defined functions in Python, Java, and Rust, allowing custom logic that isn't expressible in pure SQL. Materialize does not support UDFs.

Vector Search

RisingWave v2.6 added vector data type and similarity search, enabling AI/ML use cases like RAG systems and real-time recommendations. Materialize does not support vector operations.

Performance

Both systems are built in Rust with streaming-optimized architectures. Direct benchmarks are limited, but:

• RisingWave: Outperforms Flink in 22/27 Nexmark queries. Efficient multi-stream joins (10+ streams). Sub-second latency with checkpoint intervals as low as 1 second.
• Materialize: Based on Timely/Differential Dataflow with academic foundations for efficient incremental computation. Strict consistency adds overhead compared to eventual/snapshot models.

For most workloads, the performance difference is less significant than the architectural differences (consistency model, deployment flexibility, ecosystem integration).

Addressing Materialize's Claims About RisingWave

Materialize published a comparison page highlighting several concerns about RisingWave. Here's an honest assessment:

Claim: "RisingWave applies CDC transactions incrementally, exposing partial states." Reality: RisingWave processes CDC with snapshot consistency. Within each checkpoint (default 1 second), state is consistent. For workloads where 1-second consistency is acceptable (which is the vast majority), this is not a practical concern.

Claim: "RisingWave lacks atomic CDC transaction support for transactions exceeding 4K rows." Reality: Very large CDC transactions (>4K rows) may be split across checkpoints. For applications generating such large transactions, evaluate whether strict consistency is truly required for your use case.

Claim: "RisingWave doesn't support recursive queries." Reality: Correct. RisingWave does not support recursive CTEs. If your workload requires graph traversal or iterative computation in SQL, Materialize is a better choice.

Decision Framework

Choose RisingWave if:

• You want open-source with self-hosting flexibility
• You need Iceberg/Delta Lake integration for lakehouse architecture
• Cost efficiency matters (no SaaS premium)
• Snapshot consistency (1-second) is sufficient
• You need UDFs for custom logic
• You need MySQL CDC support
• You want vector search capabilities

Choose Materialize if:

• Strict-serializable consistency is non-negotiable (financial, regulatory)
• You need recursive CTEs for graph-like computations
• Cloud-only deployment is acceptable
• Budget is not a primary constraint
• You don't need Iceberg/Delta Lake or vector search

Frequently Asked Questions

Is RisingWave or Materialize better?

It depends on your requirements. RisingWave is better for most streaming analytics workloads — it's open source, self-hostable, supports Iceberg sinks, and costs less. Materialize is better when you need strict-serializable consistency for financial or regulatory workloads. Both use PostgreSQL-compatible SQL.

Can I self-host Materialize?

No. Materialize is only available as a managed cloud service (SaaS). The source code is available under the Business Source License (BSL), but self-hosting is not supported. RisingWave is fully self-hostable under the Apache 2.0 license.

Which has better CDC support?

RisingWave supports native CDC from both PostgreSQL and MySQL without requiring Kafka or Debezium. Materialize supports native PostgreSQL CDC and Kafka-based CDC. If you need MySQL CDC, RisingWave is the better choice.

Do both support Apache Iceberg?

RisingWave has native Iceberg sink support with 5 catalog types (REST, Hive, JDBC, Storage, S3 Tables), automatic compaction, and both Merge-on-Read and Copy-on-Write modes. Materialize does not support Iceberg sinks. For streaming lakehouse architectures, RisingWave is the clear choice.