Apache Flink is a mature, battle-tested stream processing framework with broad adoption and complex stateful processing capabilities, while RisingWave is a newer, cloud-native SQL streaming database designed for simpler real-time analytics with PostgreSQL compatibility and lower operational overhead.
Apache Flink vs RisingWave — Side-by-side comparison on A Versus B
Distributed stream processing framework with stateful computation and exactly-once guarantees.
Cloud-native SQL streaming database with PostgreSQL compatibility for real-time analytics.
First Release & Maturity. Primary Use Case. Query Language. Deployment Model. State Management. Production Users (2024). Learning Curve
Choose Apache Flink if you need enterprise-grade stream processing with complex stateful transformations, exactly-once semantics, and have teams with Java expertise — it's battle-tested across 10,000+ organizations. Choose RisingWave if you prioritize SQL simplicity, fast time-to-value for real-time analytics, PostgreSQL compatibility, and prefer cloud-managed infrastructure with minimal operational burden.
Apache Flink: 5-7 (JobManager, TaskManagers, StateBackend, Checkpoints) | RisingWave: N/A
Time to First Correct Result (learning curve)
Apache Flink: Yes (core feature) | RisingWave: N/A
Apache Flink: Exactly-once (native) | RisingWave: N/A
Apache Flink: 2-3 nodes | RisingWave: N/A
Apache Flink: 4 (Java, Scala, Python, SQL) | RisingWave: N/A
Apache Flink: Distributed snapshots + checkpointing | RisingWave: N/A
Apache Flink: Continuous streams (any size) | RisingWave: N/A
Apache Flink: 50-100ms | RisingWave: N/A
Apache Flink: Exactly-once | RisingWave: N/A
Apache Flink: Event-time, processing-time, session windows, custom | RisingWave: N/A
Apache Flink: Requires cluster with YARN/Kubernetes, moderate DevOps | RisingWave: N/A
Apache Flink: 8-12 weeks (with Kubernetes ops experience) | RisingWave: 2-3 weeks
Apache Flink: 1024 MB | RisingWave: 0.5-1 GB
Apache Flink: 10,000+ | RisingWave: 500+
Apache Flink: 4 (Java, Python, Scala, SQL) | RisingWave: 1 (SQL primary)
Apache Flink: 100-500 ms (tuning dependent) | RisingWave: 50-200 ms
Apache Flink: Terabyte-scale (tested to 10+ TB) | RisingWave: Hundred-gigabyte-scale (tested to 500 GB)
Apache Flink: 29,000+ | RisingWave: 6,500+
Apache Flink: 1.5-2.5 GB | RisingWave: N/A
Apache Flink: Native & first-class (core design) | RisingWave: N/A
Apache Flink: Limited (requires external libraries) | RisingWave: N/A
Apache Flink: 2-3 seconds (streaming) / 4-6 (batch) | RisingWave: N/A
Apache Flink: 1-100 ms (sub-second typical) | RisingWave: N/A
Apache Flink: 100,000-1,000,000 events/sec | RisingWave: N/A
Apache Flink: PyFlink added in v1.11 (2020); improved in v1.14+ | RisingWave: N/A
Apache Flink: Exactly-once (configurable per checkpoint) | RisingWave: N/A
Apache Flink: Basic REST API only (external UI required) | RisingWave: N/A
Apache Flink: Java 11+ | RisingWave: N/A
Apache Flink: ~30 native connectors | RisingWave: N/A
Apache Flink: ~200-400MB (optimized) | RisingWave: N/A
Apache Flink: Full with watermarks, out-of-order handling, allowedLateness | RisingWave: N/A
Apache Flink: ~1-2M events/sec | RisingWave: N/A
Apache Flink: Separate APIs (DataStream vs Batch) | RisingWave: N/A
Apache Flink: Memory, RocksDB, External (3 options) | RisingWave: N/A
Apache Flink: 0 (Open source) | RisingWave: N/A
Apache Flink: 12 (since 2014) | RisingWave: N/A
Apache Flink: Millions (1M+) | RisingWave: N/A
Apache Flink: 1-10ms (true event streaming) | RisingWave: N/A
Apache Flink: 1,000,000 - 5,000,000 (streaming-optimized) | RisingWave: N/A
Apache Flink: 6-8GB (efficient state management) | RisingWave: N/A
Apache Flink: 1,800,000 (StackOverflow, job postings 2024) | RisingWave: N/A
Apache Flink: 2,000+ (Flink SQL, state backends, CEP library) | RisingWave: N/A
Apache Flink: 18% (Alibaba, Netflix, Uber, Lyft use cases) | RisingWave: N/A
Apache Flink: 6-10 weeks (steeper learning curve, less documentation) | RisingWave: N/A
Apache Flink: 15-30 lines (native session window API) | RisingWave: N/A
Apache Flink: 100-500ms | RisingWave: N/A
Apache Flink: 256-512MB | RisingWave: N/A
Apache Flink: 5 types (keyed, operator, broadcast, queryable, custom) | RisingWave: N/A
Apache Flink: 8,000-12,000 | RisingWave: N/A
Apache Flink: 1-10ms (streaming native) | RisingWave: N/A
Apache Flink: 7-9 (complex) | RisingWave: N/A
Apache Flink: 2048-8192 | RisingWave: N/A
Apache Flink: Terabytes of distributed state native | RisingWave: N/A
Apache Flink: 20-40 hours (learning + development) | RisingWave: N/A
Apache Flink: Millions (100M+ with tuning) | RisingWave: N/A
Apache Flink: 2 GB (standalone single node) | RisingWave: N/A
Time-to-Production (Simple Real-time Dashboard)
Apache Flink: 3-4 weeks | RisingWave: 1-2 weeks
Apache Flink: 100-500ms | RisingWave: 50-200ms
Apache Flink: 2-3 GB | RisingWave: 4-6 GB
Apache Flink: Yes (distributed snapshots) | RisingWave: No (at-least-once only)
Apache Flink: 70% (subset with UDF limitations) | RisingWave: 95% (PostgreSQL compatible)
Apache Flink: 120-150 | RisingWave: 40-60
How to choose between Apache Flink and RisingWave
Apache Flink vs RisingWave — Structured Comparison Data
Machine-readable comparison dataset for Apache Flink vs RisingWave. Contains 95 attribute comparisons, 5 FAQ pairs.
Apache Flink vs RisingWave — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Apache Flink vs RisingWave.
When should I choose Flink over RisingWave?
Choose Flink if you need exactly-once semantics (critical for financial/payment systems), complex event processing with custom stateful logic, or have existing Java/Scala codebases. Flink's distributed snapshot mechanism guarantees no duplicate or lost events, making it essential for fraud detection, transaction processing, and CEP patterns that RisingWave cannot match.
RisingWave is production-ready for real-time analytics and materialized views (500+ organizations deployed as of 2024), but has a smaller reference customer base than Flink's 10,000+ deployments. For mission-critical financial systems requiring exactly-once guarantees, Flink remains the safer choice. RisingWave excels for analytics, dashboards, and streaming SQL where at-least-once semantics are acceptable.
Can I migrate from Flink to RisingWave or vice versa?
Limited direct migration exists. Flink uses Java/Scala DataStream APIs or SQL, while RisingWave uses PostgreSQL-compatible SQL. For simple SQL-based jobs, you can rewrite Flink SQL to RisingWave SQL (10-20% effort). For complex Flink DataStream programs with custom operators and CEP logic, a full rewrite would be required. The reverse (RisingWave to Flink) is easier due to Flink's broader feature set.
What is the cost difference between Flink and RisingWave?
RisingWave cloud-managed is SaaS pricing (~$0.50-$1.50/hour for standard clusters in 2024). Self-hosted Flink requires infrastructure costs (Kubernetes, compute, storage) typically $5,000-$50,000/month depending on scale. RisingWave's managed model is cheaper for small-to-medium workloads; Flink's self-hosted can be cheaper at massive scale (10M+ events/sec) with optimization.
How do latencies compare for real-time dashboards?
RisingWave achieves 50-200ms P99 latency for materialized view queries by default due to in-memory indexes. Flink achieves 100-500ms P99 depending on checkpointing intervals and operator logic. For sub-100ms dashboard refresh needs, RisingWave's incremental materialized views are better optimized. For complex CEP requiring Flink's stateful operators, expect higher latency due to tuning requirements.
How to Choose Between Apache Flink and RisingWave
First Release & Maturity: Apache Flink has 2011 (Apache since 2014), while RisingWave has 2021 (private beta), 2022 (public).
Primary Use Case: Apache Flink has Complex event processing, stateful transformations, CEP, while RisingWave has Real-time SQL analytics, incremental materialized views.
Query Language: Apache Flink has DataStream API (Java/Scala), SQL with limited UDF support, while RisingWave has PostgreSQL-compatible SQL (full standard support).
Deployment Model: Apache Flink has On-premise, self-managed, Kubernetes, cloud VMs, while RisingWave has Cloud-native first (cloud-managed SaaS), self-hosted beta.
State Management: Apache Flink has RocksDB, incremental checkpointing, exactly-once semantics, while RisingWave has In-memory + persistent storage, MVCC, eventual consistency.
Production Users (2024): Apache Flink has 10,000+ enterprises (Alibaba, Netflix, Uber, AWS), while RisingWave has 500+ organizations (growing adoption).
Learning Curve: Apache Flink has Steep (requires Java/Scala or SQL expertise, CEP concepts), while RisingWave has Gentle (PostgreSQL/SQL knowledge sufficient).