Alternatives · Figures checked September 2026
DataPelago alternatives (2026)
ETL Compare staff · Published 29 September 2026
In brief
On our lead ranking, the highest-ranked alternatives to DataPelago (3.14) are Apache Gluten (3.73) and DualBird (3.72). Seven of the eight alternatives have a higher ETL fit score than DataPelago and one has a lower one; the list below shows where each scores higher or lower than DataPelago.
Why do teams look for alternatives to DataPelago?
These points come from DataPelago's own public pages and the facts on our review, as of September 2026. They are reasons to compare, not complaints we collected.
- Pricing runs through the Google Cloud and AWS marketplaces, with no per-job rate you can model without a quote.
- Its page names Google Cloud and AWS but not specific managed services such as Amazon EMR, Dataproc or Databricks.
- Its page says to avoid heavy RDD and UDF use, and shuffle, spill and write behavior are not described.
- Its evidence is vendor-published, and tuning guidance and support terms are not published on the pages we reviewed.
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 DataPelago on: Stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community
- DataPelago scores higher on: tuning and operating burden
- Tied on: adoption effort
- 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 DataPelago on: Adoption effort, stage coverage and tuning and operating burden
- DataPelago 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 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 DataPelago on: Stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community
- DataPelago scores higher on: tuning and operating burden
- Tied on: adoption effort
- 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 DataPelago on: Stage coverage, cost model transparency, published evidence and maturity and community
- DataPelago scores higher on: adoption effort
- Tied on: tuning and operating burden and platform and instance portability
- 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 DataPelago on: Stage coverage, tuning and operating burden, cost model transparency, published evidence and maturity and community
- DataPelago scores higher 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 DataPelago on: Stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community
- DataPelago scores higher on: adoption effort and 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 DataPelago on: Adoption effort, tuning and operating burden and platform and instance portability
- DataPelago scores higher on: stage coverage, cost model transparency, published evidence and maturity and community
- 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
Speedata
2.61 / 5
ETL fit score (editorial assessment, 0-5)Rank 9 of 9
Teams that can add dedicated analytics hardware on premises
- Does not score higher than DataPelago on any criterion
- DataPelago scores higher on: adoption effort, stage coverage, platform and instance portability and cost model transparency
- Tied on: tuning and operating burden, published evidence and maturity and community
- Runs on: Speedata APU servers in your data center (pre-configured 2U server or OEM servers such as HPE); Amazon EMR, EKS and Databricks not mentioned on the product page
- Published price: Not published; book a demo
| Alternative | ETL fit score | Scores higher than DataPelago on | Also documented for DataPelago's platforms |
|---|---|---|---|
| Apache Gluten | 3.73 | Stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community | None documented |
| DualBird | 3.72 | Adoption effort, stage coverage and tuning and operating burden | None documented |
| DataFusion Comet | 3.67 | Stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community | None documented |
| RAPIDS Accelerator | 3.65 | Stage coverage, cost model transparency, published evidence and maturity and community | None documented |
| 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 | Stage coverage, platform and instance portability, cost model transparency, published evidence and maturity and community | None documented |
| Flarion | 3.15 | Adoption effort, tuning and operating burden and platform and instance portability | None documented |
| Speedata | 2.61 | None | None documented |
When should you stay with DataPelago?
Stay with DataPelago if your jobs are compute-intensive Spark SQL or DataFrame work on Parquet or ORC in Google Cloud or AWS, with little RDD or UDF use. DataPelago states existing Spark code runs unchanged with no data migration, and it is bought pay as you go through the cloud marketplaces. It ranks 8th of 9 on our lead ranking (3.14); run one real pipeline through a proof of concept before you rely on its figures.
Frequently asked questions
What is the best alternative to DataPelago?
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 DataPelago?
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 DataPelago?
DataPelago does not list a named Spark platform as documented on the pages we reviewed, so whether a switch means a platform move depends on where you run today. Open-source plugins without a guide for a platform can often be self-installed where you control Spark configuration.