Alternatives · Figures checked September 2026
Apache Gluten alternatives (2026)
ETL Compare staff · Published 29 September 2026
In brief
Apache Gluten has the highest ETL fit score in this edition (3.9), so every alternative scores lower overall. The closest are DataFusion Comet (3.8) and RAPIDS Accelerator (3.7), and each alternative still scores higher than Apache Gluten on some criteria, listed below.
Why do teams look for alternatives to Apache Gluten?
These points come from Apache Gluten's own public pages and the facts on our review, as of September 2026. They are reasons to compare, not complaints we collected.
- Your team sizes off-heap memory itself; the Velox getting-started page uses 20g as its example.
- Spill in the Velox backend is documented as experimental.
- Support comes from community channels; no vendor support contract is described on the project pages.
- The project does not publish guides for managed platforms such as Amazon EMR or Google Cloud Dataproc, so you install it yourself.
Which alternatives score highest?
Alternative 1
DataFusion Comet
3.8 / 5
ETL fit score (editorial assessment, 0-5)Rank 2 of 7
Best for teams on recent Spark 4.x releases
- Scores higher than Apache Gluten on: Tuning and operating burden
- Apache Gluten scores higher on: stage coverage, platform and instance portability and maturity and community
- Tied on: adoption effort, cost model transparency and published evidence
- Runs on: Self-managed Spark 3.5, 4.0 and 4.1 (3.4 deprecated) on Linux
- Published price: No license fee
Alternative 2
RAPIDS Accelerator
3.7 / 5
ETL fit score (editorial assessment, 0-5)Rank 3 of 7
Best for teams that already run GPU capacity
- Scores higher than Apache Gluten on: Stage coverage, tuning and operating burden and maturity and community
- Apache Gluten scores higher on: adoption effort, platform and instance portability, cost model transparency and published evidence
- Runs on: Amazon EMR, Databricks, Dataproc, GKE, Azure Synapse, Kubernetes, on-premises, OCI
- Published price: No plugin fee; GPU instance pricing applies
Alternative 3
DualBird
3.6 / 5
ETL fit score (editorial assessment, 0-5)Rank 4 of 7
Best for spill- and shuffle-heavy ETL on EMR and EKS
- Scores higher than Apache Gluten on: Adoption effort, stage coverage and tuning and operating burden
- Apache Gluten scores higher on: platform and instance portability, cost model transparency, published evidence and maturity and community
- Runs on: Apache Spark, Amazon EMR and Amazon EKS, on AWS
- Published price: Not published; contact DualBird
Alternative 4
Apache Auron
3.5 / 5
ETL fit score (editorial assessment, 0-5)Rank 5 of 7
Open-source option with its own shuffle and memory layer
- Does not score higher than Apache Gluten on any criterion
- Apache Gluten scores higher on: adoption effort, platform and instance portability, published evidence and maturity and community
- Tied on: stage coverage, tuning and operating burden and cost model transparency
- Runs on: Self-managed Spark on JDK 8, 11, 17 or 21
- Published price: No license fee
Alternative 5
Databricks Photon
3.4 / 5
ETL fit score (editorial assessment, 0-5)Rank 6 of 7
Best for teams already on Databricks
- Scores higher than Apache Gluten on: Tuning and operating burden and maturity and community
- Apache Gluten scores higher on: adoption effort, platform and instance portability, cost model transparency and published evidence
- Tied on: stage coverage
- Runs on: Databricks only (AWS, Azure, Google Cloud)
- Published price: Databricks DBU pricing; Photon changes DBU consumption
Alternative 6
Flarion
3.1 / 5
ETL fit score (editorial assessment, 0-5)Rank 7 of 7
Commercial plugin with a broad managed-platform list
- Scores higher than Apache Gluten on: Adoption effort and tuning and operating burden
- Apache Gluten scores higher on: stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community
- Runs on: Databricks, AWS EMR, GCP Dataproc, Azure HDInsight, on-premises
- Published price: Not on homepage; listed on AWS Marketplace
| Alternative | ETL fit score | Scores higher than Apache Gluten on | Also documented for Apache Gluten's platforms |
|---|---|---|---|
| DataFusion Comet | 3.8 | Tuning and operating burden | Self-managed Spark or Kubernetes |
| RAPIDS Accelerator | 3.7 | Stage coverage, tuning and operating burden and maturity and community | Self-managed Spark or Kubernetes |
| DualBird | 3.6 | Adoption effort, stage coverage and tuning and operating burden | Self-managed Spark or Kubernetes |
| Apache Auron | 3.5 | None | Self-managed Spark or Kubernetes |
| Databricks Photon | 3.4 | Tuning and operating burden and maturity and community | None documented |
| Flarion | 3.1 | Adoption effort and tuning and operating burden | Self-managed Spark or Kubernetes |
When should you stay with Apache Gluten?
Stay with Gluten if you self-manage Spark 3.4 to 4.1, have engineers who can own off-heap memory and shuffle settings, and want the most widely contributed open-source native engine in this set. Gluten ranks 1st of 7 in this edition (3.9), has no license fee and runs on the standard x86_64 or aarch64 instances you already use.
Frequently asked questions
What is the best alternative to Apache Gluten?
On our published weights, DataFusion Comet (3.8), followed by RAPIDS Accelerator (3.7). The best fit for you depends on your platform and your slowest stage; use the calculator to apply your own weights.
Is there a free alternative to Apache Gluten?
Yes. DataFusion Comet, RAPIDS Accelerator and Apache Auron are released under the Apache License 2.0 with no license fee. Free to license is not free to run: you still pay for compute, and for the engineering time to tune and support them.
Do I have to change platforms to switch from Apache Gluten?
Not necessarily. On the pages we reviewed, DataFusion Comet, RAPIDS Accelerator, DualBird, Apache Auron and Flarion are documented for self-managed Spark or Kubernetes, as Apache Gluten is. Open-source plugins without a guide for a platform can often be self-installed where you control Spark configuration.