Tools · Figures checked September 2026
Spark accelerator calculator: re-weight the scores for your team
ETL Compare staff · Published 29 September 2026
In brief
Move the seven sliders to reflect what matters to your team, and the ranking of the seven Spark accelerators recomputes from our published criterion scores. With our default weights the order matches the rankings page, led by Apache Gluten (3.9). No product in this set publishes a per-unit price, so the calculator shows each vendor's published price terms instead of computing a cost.
The ETL fit score is a weighted average of seven editorial criterion scores. Our weights favour adoption effort and stage coverage because this site covers speeding up Spark ETL you already run. Your team may weigh things differently: a team with no one to tune memory settings may care more about operating burden, and a team whose procurement rules require a public price may care more about cost model transparency. The sliders apply your weights to the same scores.
What matters to your team?
How much work to run an existing Spark ETL job on it, starting from the platform you already use? No code changes, few setup steps and no platform move score high.
Which stages of an ETL job (read, transform, shuffle, spill, write) does the vendor's own documentation say it addresses, and what happens to unsupported operations?
After install, how much memory sizing, configuration and troubleshooting falls on your team, and who supports you when a job fails?
How many Spark platforms is it documented for, and does it run on the instance types you already use?
Can you work out what it costs before a sales call: license or fee, plus any change in instance price?
Are performance figures published with enough setup detail to reproduce, and has anyone other than the vendor published results?
How long has it been in use, who contributes, and how visible is its production track record?
Documented means the vendor or project lists the platform on the pages we reviewed. Self-install means you can usually add an open-source plugin to a platform that lets you set Spark configuration and classpath, but the project does not publish a guide for that platform. None of the vendor pages we reviewed list AWS Glue.
How do the accelerators rank on your weights?
| Rank | Accelerator | Your score | Our score | Change in rank | Platform | License | Published price |
|---|---|---|---|---|---|---|---|
| 1 | Gluten + Velox | 3.85 | 3.9 | No change | Any | Apache License 2.0 | No license fee |
| 2 | Comet | 3.78 | 3.8 | No change | Any | Apache License 2.0 | No license fee |
| 3 | RAPIDS Accelerator | 3.71 | 3.7 | No change | Any | Apache License 2.0 | No plugin fee; GPU instance pricing applies |
| 4 | DualBird | 3.60 | 3.6 | No change | Any | Commercial | Not published; contact DualBird |
| 5 | Auron | 3.54 | 3.5 | No change | Any | Apache License 2.0 | No license fee |
| 6 | Photon | 3.39 | 3.4 | No change | Any | Commercial (part of Databricks) | Databricks DBU pricing; Photon changes DBU consumption |
| 7 | Flarion | 3.06 | 3.1 | No change | Any | Commercial | Not on homepage; listed on AWS Marketplace |
How the score is computed
Your score = (A x w1 + S x w2 + T x w3 + P x w4 + C x w5 + E x w6 + M x w7) / (w1 + w2 + w3 + w4 + w5 + w6 + w7)
A, S, T, P, C, E and M are our 0-5 scores for adoption effort, stage coverage, tuning and operating burden, platform and instance portability, cost model transparency, published evidence and maturity and community. w1 to w7 are your slider values. The default sliders (10, 10, 7.5, 5, 5, 7.5 and 5) give the same result as our published weights of 20, 20, 15, 10, 10, 15 and 10 percent, because only the ratios between weights matter.
Your weights as shares: Adoption effort 20%, Stage coverage 20%, Tuning and operating burden 15%, Platform and instance portability 10%, Cost model transparency 10%, Published evidence 15%, Maturity and community 10%
Why is there no cost column?
Prices in the table are shown as each vendor or project publishes them. The open-source plugins have no license fee, the RAPIDS Accelerator's cost is GPU instance time, Photon is billed through Databricks DBUs, and DualBird and Flarion do not publish prices on the pages we reviewed. None of these is a per-unit price we could multiply by a job size, so the calculator does not invent one. To compare cost on your own job, use cost per run: see Spark cost per job, explained.
Frequently asked questions
How do I use the calculator?
Move each slider from 0 (ignore this criterion) to 10 (matters most). The table re-ranks as you move them, and the Change in rank column shows how far each product moved from our published order. "Reset to our weights" returns to the defaults.
Why do the sliders start where they do?
The defaults are our published weights divided by two, so 20% becomes 10, 15% becomes 7.5 and 10% becomes 5. The starting ranking is therefore the same as on the rankings page.
Can I change the criterion scores?
No. The calculator changes weights, not scores. Each score and its one-line reason is on the vendor's review, and corrections with a public source can go to editors@etlcompare.com.
Does a higher score mean a faster product?
No. The ETL fit score measures fit for speeding up existing Spark ETL without rewriting pipelines. It is not a benchmark. To compare speed and cost, test on one of your own pipelines: see how to run a Spark accelerator proof of concept.
Scores are editorial assessments from public vendor material; prices are as published on the pages we reviewed on 27 September 2026.