Apache Arrow DataFusion vs Starburst Enterprise Context Layer
Apache Arrow DataFusion
datafusion.apache.orgStarburst Enterprise Context Layer
starburst.ioSide by side
| Figure | Apache Arrow DataFusion | Starburst Enterprise Context Layer |
|---|---|---|
| Price from | Free | $0.50/mo |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | — | Yes |
| macOS | Yes | — |
| Linux | Yes | — |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 7 |
| Spec score · Query Engine Software | 8.0 (#10) | 8.5 (#5) |
| Support | The project directs users to its community communication channels for getting in touch. | Enterprise support tiers range from five portal tickets monthly to unlimited tickets and dedicated experts; Sev-1 response targets range from one hour to 30 minutes. |
Plans
Starburst Enterprise Context Layer
- FreeFree
- ProPriced on request
- Pro$0.50 a month
- EnterprisePriced on request
- Enterprise$0.75 a month
- Mission-CriticalPriced on request
- Mission-Critical$1 a month
In their own words
Apache Arrow DataFusion
Apache Arrow DataFusion is a free, extensible query engine written in Rust that uses Apache Arrow as its in-memory format. It is intended for developers building database and analytics systems tailored to particular workloads, rather than as a ready-made hosted database. Queries run in-process, using threads for parallel execution. DataFusion offers SQL and DataFrame APIs, while related subprojects provide Python and Java interfaces. Documented capabilities include SQL parsing and planning, parallel and streaming execution, and query optimization. Built-in data sources include CSV, Parquet, JSON, Avro, and Arrow. Developers can add sources through the TableProvider trait and customize functions, operators, and other components. Runtime features include enforced memory limits and disk spilling for sorts, grouping, and joins. The core project is designed for in-process use; Ballista is a related distributed processing extension. Rust users commonly add DataFusion from crates.io, while official Apache releases are source artifacts. The project recommends verifying release artifacts with an OpenPGP signature or SHA-512 checksum.
Starburst Enterprise Context Layer
Starburst Enterprise Context Layer turns scattered data into governed, versioned Data Products. Each product combines a dataset with business definitions, ownership, access policies, and lineage, and appears in a shared catalog. Controls include role-based access, column masking, and row-level security. Teams can define products in YAML, commit them to git, test changes before merging, and roll back; breaking changes are reviewed before rollout. Automated CI/CD lineage checks verify upstream freshness before a new version is published. A semantic layer turns raw data into business-ready metrics, dimensions, and relationships for BI tools and AI agents. Products can be consumed through JDBC or REST, and the platform connects to more than 50 sources, including Apache Iceberg, Delta Lake, Hive, Amazon S3, Snowflake, and PostgreSQL. It runs in private cloud, hybrid, or on-premises environments and is air-gap ready. The free plan is free. Pro costs what you agree with the maker, billed /credit; Enterprise costs what you agree with the maker, billed /credit; Mission-Critical costs what you agree with the maker, billed /credit.