Where Data Becomes
Intelligence
Unified open-source framework for batch, stream, and AI workloads.
Rethink Spark.
Meet Sail.
A drop-in Apache Spark replacement, reimagined for modern data and AI infrastructure.
Built in Rust, Sail delivers unmatched performance, lower costs, and a familiar Apache Spark interface—all in a unified, cloud-native engine.
- 94% Lower Cost Save big on your cloud bill or achieve more with the same budget.
- 0 Code Changes Required Use familiar Spark SQL and DataFrame APIs without complex migration efforts.
- 4x Faster Execution Get insights from your data instantly and gain value from it frequently.
- 0 JVMs Enjoy the Rust-native engine with no memory hogs and no garbage collection pauses.
One Engine.
Every Workload.
A unified solution that scales from your laptop to the cloud.
- Unified Architecture A single entrypoint for batch, streaming, and AI. One solution for them all.
- Composable Data Stack Bring compute closer to your data lakehouse and AI models. Need an integration? We’ll build it.
- Parity with Apache Spark Use your existing Spark code. Only switch the endpoint. No rewrites, no headaches.
- Cloud-Native by Design Autoscaling, observability, and decoupled storage are planned from the start.
- Rust at the Core Memory management and concurrency renovated. Performant, efficient, and safe.
- Lightning-fast UDFs Ditch the Py4J bridge and give your Python code a natural feel in query execution.
See the Difference:
Performance. Efficiency. Simplicity.
Unlock greater possibilities across the board.
Spark | Sail | |
---|---|---|
• Query Time | Baseline | Up to 8x faster |
• Memory Usage | ~54 GB average | ~22 GB peak |
• Disk Spill | > 110 GB | 0 GB |
• Cost Efficiency | Baseline | 4x faster at 6% cost |
• Engine | JVM-based | Rust-native |
• Python Bindings | Inter-process | In-process |
• Cluster Startup Time | Several minutes | A few seconds |
Built for Speed.
Ready for Scale.
Try Sail and see what modern data processing feels like.