Alternatives · Figures checked September 2026
Speedata alternatives (2026)
ETL Compare staff · Published 29 September 2026
In brief
On our lead ranking, the highest-ranked alternatives to Speedata (2.61) are Apache Gluten (3.73) and DualBird (3.72). Eight of the eight alternatives have a higher ETL fit score than Speedata and zero have a lower one; the list below shows where each scores higher or lower than Speedata.
Why do teams look for alternatives to Speedata?
These points come from Speedata's own public pages and the facts on our review, as of September 2026. They are reasons to compare, not complaints we collected.
- It runs on servers fitted with Speedata C200 APU cards in your own data center, so a trial means adding dedicated hardware rather than reusing the instances a job runs on today.
- Amazon EMR, EKS, Databricks and Kubernetes are not mentioned on the product page.
- There is no pricing page and no public price for the software or the APU servers; a demo and a quote are needed.
- Setup detail for its vendor figures is not published, and support terms are not published.
Which alternatives score highest?
Alternative 1
Apache Gluten
3.73 / 5
ETL fit score (editorial assessment, 0-5)Rank 1 of 9
Open-source native engine for self-managed Spark
- Scores higher than Speedata on: Adoption effort, stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community
- Speedata scores higher on: tuning and operating burden
- Runs on: Self-managed Spark 3.4 to 4.1 on Linux, on any platform where you control Spark config
- Published price: No license fee
Alternative 2
DualBird
3.72 / 5
ETL fit score (editorial assessment, 0-5)Rank 2 of 9
Best for spill- and shuffle-heavy ETL on EMR and EKS
- Scores higher than Speedata on: Adoption effort, stage coverage, tuning and operating burden and platform and instance portability
- Speedata scores higher on: published evidence and maturity and community
- Tied on: cost model transparency
- Runs on: Apache Spark, Amazon EMR and Amazon EKS, on AWS
- Published price: Not published; contact DualBird
Alternative 3
DataFusion Comet
3.67 / 5
ETL fit score (editorial assessment, 0-5)Rank 3 of 9
Best for teams on recent Spark 4.x releases
- Scores higher than Speedata on: Adoption effort, stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community
- Speedata scores higher on: tuning and operating burden
- Runs on: Self-managed Spark 3.5, 4.0 and 4.1 (3.4 deprecated) on Linux
- Published price: No license fee
Alternative 4
RAPIDS Accelerator
3.65 / 5
ETL fit score (editorial assessment, 0-5)Rank 4 of 9
Best for teams that already run GPU capacity
- Scores higher than Speedata on: Adoption effort, stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community
- Speedata does not score higher on any criterion
- Tied on: tuning and operating burden
- Runs on: Amazon EMR, Databricks, Dataproc, GKE, Azure Synapse, Kubernetes, on-premises, OCI
- Published price: No plugin fee; GPU instance pricing applies
Alternative 5
Databricks Photon
3.46 / 5
ETL fit score (editorial assessment, 0-5)Rank 5 of 9
Best for teams already on Databricks
- Scores higher than Speedata on: Stage coverage, tuning and operating burden, cost model transparency, published evidence and maturity and community
- Speedata does not score higher on any criterion
- Tied on: adoption effort and platform and instance portability
- Runs on: Databricks only (AWS, Azure, Google Cloud)
- Published price: Databricks DBU pricing; Photon changes DBU consumption
Alternative 6
Apache Auron
3.42 / 5
ETL fit score (editorial assessment, 0-5)Rank 6 of 9
Open-source option with its own shuffle and memory layer
- Scores higher than Speedata on: Adoption effort, stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community
- Speedata scores higher on: tuning and operating burden
- Runs on: Self-managed Spark on JDK 8, 11, 17 or 21
- Published price: No license fee
Alternative 7
Flarion
3.15 / 5
ETL fit score (editorial assessment, 0-5)Rank 7 of 9
Commercial plugin with a broad managed-platform list
- Scores higher than Speedata on: Adoption effort, stage coverage, tuning and operating burden and platform and instance portability
- Speedata scores higher on: published evidence and maturity and community
- Tied on: cost model transparency
- Runs on: Databricks, AWS EMR, GCP Dataproc, Azure HDInsight, Spark on Kubernetes, on-premises
- Published price: Usage-based, per CPU-hour: $0.004 self-hosted cloud, $0.007 on managed Spark (EMR, GCP Managed Spark, Azure HDInsight), $0.008 on Databricks; on-premise $0.50 per CPU-month.
Alternative 8
DataPelago
3.14 / 5
ETL fit score (editorial assessment, 0-5)Rank 8 of 9
Compute-heavy Spark SQL and DataFrame jobs on Parquet or ORC in Google Cloud or AWS
- Scores higher than Speedata on: Adoption effort, stage coverage, platform and instance portability and cost model transparency
- Speedata does not score higher on any criterion
- Tied on: tuning and operating burden, published evidence and maturity and community
- Runs on: Multiple Spark versions on Google Cloud and AWS; Amazon EMR, EKS and Databricks not named on the DPA-S page
- Published price: Pay as you go through the Google Cloud and AWS marketplaces; the AWS Marketplace listing shows a vCPU-hour dimension and a $100,000 per month one-month contract entry
| Alternative | ETL fit score | Scores higher than Speedata on | Also documented for Speedata's platforms |
|---|---|---|---|
| Apache Gluten | 3.73 | Adoption effort, stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community | Self-managed Spark or Kubernetes |
| DualBird | 3.72 | Adoption effort, stage coverage, tuning and operating burden and platform and instance portability | Self-managed Spark or Kubernetes |
| DataFusion Comet | 3.67 | Adoption effort, stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community | Self-managed Spark or Kubernetes |
| RAPIDS Accelerator | 3.65 | Adoption effort, stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community | Self-managed Spark or Kubernetes |
| Databricks Photon | 3.46 | Stage coverage, tuning and operating burden, cost model transparency, published evidence and maturity and community | None documented |
| Apache Auron | 3.42 | Adoption effort, stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community | Self-managed Spark or Kubernetes |
| Flarion | 3.15 | Adoption effort, stage coverage, tuning and operating burden and platform and instance portability | Self-managed Spark or Kubernetes |
| DataPelago | 3.14 | Adoption effort, stage coverage, platform and instance portability and cost model transparency | None documented |
When should you stay with Speedata?
Stay with Speedata if you run Spark on premises and can add servers fitted with Speedata C200 APU cards, bought pre-configured or through OEM partners such as HPE. Speedata states Dash drops into existing Spark environments with zero code changes, and its Workload Analyzer reads your Spark logs. It ranks 9th of 9 on our lead ranking (2.61); ask for a demo, a quote and the setup behind its figures before you decide.
Frequently asked questions
What is the best alternative to Speedata?
On our lead weights, Apache Gluten (3.73), followed by DualBird (3.72). 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 Speedata?
Yes. Apache Gluten, 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 Speedata?
Not necessarily. On the pages we reviewed, Apache Gluten, DualBird, DataFusion Comet, RAPIDS Accelerator, Apache Auron and Flarion are documented for self-managed Spark or Kubernetes, as Speedata is. Open-source plugins without a guide for a platform can often be self-installed where you control Spark configuration.