Head to head · Figures checked September 2026
Flarion vs Databricks Photon
ETL Compare staff · Figures checked September 2026 · Sourced from vendor docs, project pages and public benchmarks · Published 29 September 2026
In brief
Databricks Photon has the higher ETL fit score on our published weights (3.4 against 3.1 out of 5). Flarion scores higher on adoption effort and platform and instance portability; Databricks Photon scores higher on stage coverage, tuning and operating burden, cost model transparency, published evidence and maturity and community. Photon only runs inside Databricks, so for most teams the platform they use decides this comparison before the scores do.
On our weights Databricks Photon ranks 6th of 7 and Flarion ranks 7th of 7. Which one fits depends on the criteria below and on the platform you run.
Flarion is a commercial DataFusion-based, Arrow-native execution engine for Spark, Hadoop and Ray. Databricks Photon is a Databricks-native vectorized C++ query engine inside the Databricks Runtime. Neither requires changes to Spark SQL or DataFrame code, according to its own documentation.
3.1 / 5
ETL fit score (editorial assessment, 0-5)ETL fit score (editorial assessment, 0-5)
Rank 7 of 7
Commercial plugin with a broad managed-platform list
3.4 / 5
ETL fit score (editorial assessment, 0-5)ETL fit score (editorial assessment, 0-5)
Rank 6 of 7
Best for teams already on Databricks
How do Flarion and Databricks Photon score on each criterion?
| Criterion | Flarion | Photon | Higher score |
|---|---|---|---|
| Adoption effort 20% | 4.2 | 2.6 | Flarion |
| Stage coverage 20% | 2.8 | 3.8 | Photon |
| Tuning and operating burden 15% | 3.8 | 4.6 | Photon |
| Platform and instance portability 10% | 4.2 | 1.6 | Flarion |
| Cost model transparency 10% | 2.0 | 3.2 | Photon |
| Published evidence 15% | 1.8 | 3.2 | Photon |
| Maturity and community 10% | 2.0 | 4.6 | Photon |
| ETL fit score | 3.1 | 3.4 | Photon |
Why each score
- Adoption effort
- Flarion (4.2): Flarion states "zero code and infrastructure changes" and a 6-minute setup by adding configuration parameters.
- Photon (2.6): One checkbox (or on by default on serverless) with no code changes if you already run on Databricks; for a team on EMR or self-managed Spark it means moving to Databricks first.
- Stage coverage
- Flarion (2.8): Describes a DataFusion-based, Arrow-native execution engine plus caching; shuffle, spill and write behavior are not described on the pages we reviewed.
- Photon (3.8): Documents native scans (Parquet, Delta, CSV, JSON), filters, joins, aggregates, windows and writes, with fallback to the Spark runtime; no UDF, RDD or stateful streaming support.
- Tuning and operating burden
- Flarion (3.8): A commercial product with performance monitoring and anomaly detection described; support terms are not published.
- Photon (4.6): Managed by Databricks inside its runtime, so there is no plugin for your team to install or version.
- Platform and instance portability
- Flarion (4.2): Lists Databricks, AWS EMR, GCP Dataproc, Azure HDInsight and on-premises, on standard instances.
- Photon (1.6): Available only inside Databricks (on AWS, Azure and Google Cloud).
- Cost model transparency
- Flarion (2.0): Listed on AWS Marketplace; no price on the homepage.
- Photon (3.2): Databricks publishes DBU rates, but Photon compute consumes DBUs at different rates, so the net effect has to be modelled per job.
- Published evidence
- Flarion (1.8): Headline figures (3x performance, 60% cost reduction) without a published methodology on the pages we reviewed.
- Photon (3.2): Databricks documents where Photon does not help (queries under two seconds, UDFs); performance comparisons outside Databricks are not possible because it only runs there.
What do Flarion and Databricks Photon cost, as published?
| Flarion | Photon | |
|---|---|---|
| License | Commercial | Commercial (part of Databricks) |
| Published price | Not on homepage; listed on AWS Marketplace | Databricks DBU pricing; Photon changes DBU consumption |
| Instances | Standard instances | Supported Databricks instance types, including Graviton |
| Runs on | Databricks, AWS EMR, GCP Dataproc, Azure HDInsight, on-premises | Databricks only (AWS, Azure, Google Cloud) |
| Code changes | None stated; configuration parameters | None on Databricks; platform move otherwise |
Prices and terms as published on the pages we reviewed, 27 September 2026. Neither vendor's figure is a quote.
Sources: flarion.io, Photon documentation · Fetched 27 Sep 2026
Where are they documented to run?
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.
Which job stages does each address?
| Accelerator | Read | Transform | Shuffle | Spill | Write |
|---|---|---|---|---|---|
| Photon | Documented | Documented | Not stated | Not stated | Documented |
| Flarion | Partial | Documented | Not stated | Not stated | Not stated |
- Documented: the vendor's own documentation says it addresses this stage
- Partial: indirect or experimental, or covered only by an end-to-end claim
- Not stated: not found on the pages we reviewed
This shows what each vendor says, not what we measured. Sources are listed on each review.
Choose Flarion if
- You want a commercial plugin that Flarion states needs zero code and infrastructure changes
- You need one commercial product across Databricks, Amazon EMR, Google Cloud Dataproc, Azure HDInsight and on-premises
- You run on Amazon EMR, Databricks, Google Cloud (Dataproc) and self-managed Spark or Kubernetes
Choose Databricks Photon if
- Your jobs already run on Databricks and you want no plugin to install or version
- You want the engine that is the default on Databricks serverless and SQL warehouses
- You run on Databricks
Frequently asked questions
Which has the higher ETL fit score, Flarion or Databricks Photon?
Databricks Photon, with 3.4 against 3.1 out of 5 on our published weights. Flarion scores higher on adoption effort and platform and instance portability and Databricks Photon on stage coverage, tuning and operating burden, cost model transparency, published evidence and maturity and community. The score measures fit for speeding up existing Spark ETL, not raw speed.
Do Flarion and Databricks Photon run on the same platforms?
Both are documented for Databricks. Flarion is also documented for Amazon EMR, Google Cloud (Dataproc) and self-managed Spark or Kubernetes.
What do Flarion and Databricks Photon cost?
Flarion: Not on homepage; listed on AWS Marketplace (Commercial). Databricks Photon: Databricks DBU pricing; Photon changes DBU consumption (Commercial (part of Databricks)). For a like-for-like comparison, work out cost per run on one of your own jobs: see Spark cost per job, explained.