What is Feathr?
A data engineering framework that enables teams to build feature transformations, register and catalog them centrally, and compute them correctly for AI training and production inference. It provides batch and streaming feature computation with integration to Databricks, Azure Synapse, and other data platforms.
Feathr pricing
We don't have Feathr's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
What Feathr does
The capabilities that matter for feature stores, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Point in time correctness
- ✓
- Feature registry catalog
- ✓
- Streaming features
- ✓
- On demand transforms
- ✓
- Deployment model
- Self hosted
- Drift monitoring
- ✓
- Embeddings vector support
- ✓
- Multi cloud
- ✓
- RBAC governance
- ✓
- Lineage tracking
- ✓
- Pricing model
- Open source self host
Platform & deployment
Independently observed- CLI
- Web
- Cloud / SaaS
- Self-hosted
Integrations (6)
Independently observed- Databricks
- Azure Synapse
- HDFS
- Snowflake
- PySpark
- Spark SQL
Security & compliance
Known vulnerabilities: 0 (0 in the last 12 months) sourcea count reflects scale & disclosure, not quality
Feathr alternatives
Other feature stores we track, ranked by the same independent score.
- Amazon SageMaker Feature StoreA managed repository for storing, sharing, and reusing machine learning features across your ML lifecyclemedium · 62%
- Feastlow · 28%
- TectonReal-time data platform for production AI agentslow · 6%
- Featureformlow · 22%
- Hopsworks Feature StoreA platform for managing machine learning features, model artifacts, and real-time inference serving across the full ML lifecyclelow · 26%
- Vertex AI Feature StoreA metadata management layer for storing and serving machine learning features from BigQuery data sourceslow · 3%
Compare Feathr
Side by side against other feature stores, attribute by attribute, with a source on every value.
The Vioscale score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Feathr, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Capabilities | 96 | 0.08 | 8.1 | ✓ |
| Pricing transparency | 80 | 0.08 | 6.7 | ✓ |
| Price level | 100 | 0.05 | 5.2 | ✓ |
| Release cadence | 88 | 0.05 | 4.6 | ✓ |
| Integrations | 24 | 0.09 | 2.3 | ✓ |
| Stars | 62 | 0.03 | 1.6 | ✓ |
| Dependent projects | 5 | 0.06 | 0.3 | ✓ |
| Reliability | 0 | 0.07 | 0.0 | - |
| Development activity | 0 | 0.09 | 0.0 | ✓ |
| Security posture | 0 | 0.07 | 0.0 | - |
| Package downloads | 0 | 0.14 | 0.0 | - |
| Security score | 0 | 0.04 | 0.0 | - |
| Developer Q&A activity | 0 | 0.06 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 0 | mediumsource · 2026-08-26 · 65% |
Adoption
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Multi cloud: Yes · Pricing model: open-source-self-host · Rbac governance: Yes · Deployment model: self-hosted · Drift monitoring: Yes · Lineage tracking: Yes | mediumsource · 2026-08-21 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 6 | mediumsource · 2026-08-21 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Scala | highsource · 2026-08-26 · 90% |
License
| Attribute | Value | Evidence |
|---|---|---|
| Spdx | Apache-2.0 | highsource · 2026-08-26 · 95% |
Pricing
Release
Security
| Attribute | Value | Evidence |
|---|---|---|
| Vulnerabilities | Count: 0 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=feathr&per_page=100 · Last 12m: 0 | highsource · 2026-08-26 · 90% |