Compare Spark engines
Compare pricing models, deployment options, and engine capabilities across Quanton, Databricks Photon, OSS Spark, Apache DataFusion Comet, and Apache Gluten.
For rates and a workload cost estimate, use the pricing calculator. For benchmark setup and reproduction steps, see Benchmarking.
Feature comparison
Scroll horizontally to compare all six options.
| Capability | Quanton | Databricks Classic | Databricks Serverless | OSS Spark | Apache DataFusion Comet | Apache Gluten |
|---|---|---|---|---|---|---|
| Pricing model | Per-GiB processed | DBU × compute hours | DBU × compute hours, EC2 bundled | Free engine, pay for EC2 hours | Free engine | Free engine |
| Runs in your VPC | Yes | Yes (BYOC) | No — Databricks-hosted | Yes | Yes | Yes |
| EC2 discounts (RI/spot) stay yours | Yes | Yes | No | Yes | Yes | Yes |
| Vectorized execution | Optimized and reimplemented Velox operators | Photon (closed) | Photon (closed) | No | OSS DataFusion operators | Vanilla OSS Velox |
| Storage-aware planning | Iceberg + Hudi metadata | Delta-focused | Delta-focused | No | No | No |
| Scan speedup | Yes — optimized I/O, lower scheduling overhead | Yes | Yes | No | No | No |
| Index-aware joins | Yes — new relational operator that cuts join cost | No | No | No | No | No |
| Query plan optimization | Advanced plan reshaping | Yes | Yes | Limited | Limited | Limited |
| Native columnar MERGE / compaction | Yes (~4× faster) | Delta only | Delta only | No | No | No |
| Dynamic acceleration | Yes — dynamic index maintenance | No | No | No | No | No |
| Memory-pressure resiliency | Optimized memory allocator, smart spilling | Yes | Yes | Spark default | OOMs on q67/q93 | OOMs on q67/q93 |
| AI Spark engineer in Spark UI | Yes — free, works across all engines | Limited | Limited | No | No | No |
| Reversible — point back to OSS Spark | One config line | Locked in by Databricks SQL extensions | Locked in by Databricks SQL extensions | N/A | Yes | Yes |
The Comet and Gluten memory-pressure results refer to q67 and q93 in the TPC-DS 10 TB benchmark. The compaction speedup is a separate workload result from the overall Spark execution speedup.