ETL CompareETL Compare

Head to head · Figures checked September 2026

DualBird vs Apache Gluten with Velox

ETL Compare staff · Figures checked September 2026 · Sourced from vendor docs, project pages and public benchmarks

In brief

Gluten scores higher overall (3.9 against 3.6) because it is free, portable and broadly contributed. DualBird scores higher on the three criteria that decide day-to-day effort: adoption (4.6 against 3.8), stage coverage (4.8 against 3.8) and tuning and operating burden (4.4 against 2.6). The choice comes down to whether you would rather pay a vendor or staff the tuning.

Gluten for self-managed Spark teams with engineers to tune it; DualBird for EMR and EKS teams whose jobs spill and who want a supported product.

DualBird

3.6 / 5

ETL fit score (editorial assessment, 0-5)

ETL fit score (editorial assessment, 0-5)

Rank 4 of 7

Best for spill- and shuffle-heavy ETL on EMR and EKS

Gluten + Velox

3.9 / 5

ETL fit score (editorial assessment, 0-5)

ETL fit score (editorial assessment, 0-5)

Rank 1 of 7

Highest ETL fit score: open-source native engine for self-managed Spark

Side-by-side

DualBird and Gluten + Velox compared. A filled square marks the higher score.
 DualBirdGluten + Velox
Adoption effort 20%4.6Higher3.8
Stage coverage 20%4.8Higher3.8
Tuning and operating burden 15%4.4Higher2.6
Platform and instance portability 10%2.44.3Higher
Cost model transparency 10%2.05.0Higher
Published evidence 15%2.83.8Higher
Maturity and community 10%2.04.4Higher
ETL fit score3.63.9Higher
ApproachCommercial Spark plugin paired with Amazon EC2 F2 instances, aimed at spill, skew and shuffle bottlenecksOpen-source plugin that offloads Spark SQL execution to a native C++ engine (Velox or ClickHouse)
InstancesAmazon EC2 F2Standard CPU, x86_64 or aarch64
PlatformsSpark, EMR, EKS on AWSSelf-managed Spark 3.4 to 4.1
LicenseCommercialApache 2.0
PriceNot publishedNo license fee
SetupInstance type plus pluginJar, spark.plugins, off-heap memory, ColumnarShuffleManager
Spill handlingDualBird states it eliminates disk spillsSpill in the Velox backend documented as experimental
SupportVendorCommunity

Which job stages does each address?

Spark ETL job stages and which stages each accelerator documents addressingA waterfall of five Spark ETL job stages (read, transform, shuffle, spill, write) with illustrative proportions, and below it a grid showing, for each accelerator, whether its own documentation says it addresses that stage.Anatomy of a Spark ETL jobRead: scan and decode filesTransform: filter, join, aggregateShuffle: write and fetch between stagesSpill: memory pressure pushes data to diskWrite: encode and commit outputIllustrative proportions, not measured data. Your own split comes from the Spark UI: see Profile a slow Spark job.
Stage coverage by accelerator, from vendor documentation
AcceleratorReadTransformShuffleSpillWrite
Gluten + VeloxPartialPartialDocumentedDocumentedDocumentedDocumentedPartialPartialNot statedNot stated
DualBirdPartialPartialDocumentedDocumentedDocumentedDocumentedDocumentedDocumentedPartialPartial
  • DocumentedDocumented: the vendor's own documentation says it addresses this stage
  • PartialPartial: indirect or experimental, or covered only by an end-to-end claim
  • Not statedNot stated: not found on the pages we reviewed

This shows what each vendor says, not what we measured. Sources are listed on each review.

Where does each one save time?

Gluten saves compute time on the CPUs you already pay for, but it adds engineering time: off-heap memory has to be sized, the shuffle manager switched and spill behavior watched. DualBird aims to save both compute time and tuning time, according to DualBird, at the cost of moving to F2 instances and paying a fee.

Which one handles spill-heavy jobs better?

On documentation, DualBird: spill is the centre of its product page and technical writing, while Gluten documents spill in the Velox backend as experimental. On evidence, neither has third-party results for spill-heavy ETL. If spill dominates your jobs (check Shuffle spill (disk) in the Spark UI), test both on that job.

Which one is the safer long-term bet?

Gluten, on maturity: an Apache top-level project since March 2026 with contributors from several large companies. DualBird is a young commercial product. Removing either leaves your Spark code intact, which limits lock-in in both cases.

Choose DualBird if

  • You are on EMR or EKS
  • You do not want to own memory tuning
  • Spill and shuffle dominate runtime
  • Vendor support matters

Choose Gluten if

  • You self-manage Spark
  • You have engineers for tuning
  • You want no license fee and standard instances
  • You may run outside AWS

Frequently asked questions

Can I run Gluten on Amazon EMR?

The project does not publish an EMR guide. As a Spark plugin it can generally be added where you control Spark configuration and classpath, but you own the setup.

Is DualBird built on Gluten or Velox?

DualBird does not say so on the pages we reviewed. It describes its own execution approach on F2 instances.

Sources

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