Antvia
vs Databricks
Databricks is the strongest platform in the category for machine learning. If machine learning is not what you are doing, most of what you would pay for goes unused.
Who arrives here
Databricks came up because somebody said lakehouse, and it is the name most associated with the word. Then the proposal arrived with a notebook environment, a Spark cluster and an assumption that you have engineers who work in Python.
What each one charges for
| They charge you for | Databricks | Antvia | Why it matters |
|---|---|---|---|
| Compute and volume | Charged | Not charged | More data or more refreshes, bigger bill |
| Users | Not charged | Not charged | Every extra reader costs money, forever |
| Queries | Indirect | Not charged | Asking more questions costs more |
| Sources | Not charged | Charged | Each maintained connection meters |
| Metrics | Not charged | Charged | Each published definition meters |
Where each one stops
A scope comparison, not a quality one. Databricks is very good at what it covers.
Databricks is genuinely excellent across ingest, transform and govern. It was never built to serve dashboards to two hundred non-technical people, and it has nothing at all to say about whether a decision you made last quarter was worth making.
The honest split
- A business user builds a view without a notebook, a cluster or Spark
- Governance and BI in the same price rather than as separate decisions
- No Spark skills required anywhere in the organisation
- Predictable monthly cost
- Serious machine learning and data science, which is not a claim Antvia makes
- Notebook-native work for teams who live in Python and Spark
- Streaming at genuine scale
- Unity Catalog across a large and varied estate
Who has to touch it
This is the practical difference. A Databricks deployment expects a data engineer to build pipelines, an analytics engineer to model, and somebody comfortable with clusters to keep it running. Those are three hires, and in most mid-market businesses they are three hires that have not happened.
Antvia expects one platform owner and a business user. The business user picks measures and dimensions, or asks in plain English, and cannot construct a wrong number because the wrong numbers are not expressible.
When Databricks is the right answer
Machine learning at any serious level. Streaming at scale. A team that already lives in notebooks and would experience our guardrails as a cage. Unity Catalog across a large and varied estate. In all of those cases Databricks is the better tool and we would tell you so on the call.
Questions we get asked
Do you do machine learning? No. We make data an ML team can trust, and we onboard an agent or a training job the same governed way we onboard a person. The modelling itself is not our product.
Can we use both? Yes. Databricks for data science, Antvia for governed reporting and the decision loop, reading the same gold layer.