Databricks vs Langfuse
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Databricks is the stronger AI pick in MLOps Platforms: it has a visibility score of 46.2 versus 0.3 for Langfuse, and ranks ahead in 100% of the answers that name both.
Choose Databricks if…
- You want the brand AI engines rank higher (46.2 vs 0.3)
- You need ISO 27017 or ISO 27018 or ISO 27701 or SOC 1 or SOC 3 coverage
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
Choose Langfuse if…
- AI answers describe it more positively (50% vs 35% positive)
- You need a self-hosted or on-premises option
- You need HIPAA-ready region or GDPR coverage
- Discounted cloud pricing for qualifying early-stage startups
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Databricks | Langfuse |
|---|---|---|
| Visibility score | 46.2% | 0.3% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #2 | #51 |
| Share of voice | 7.6% | 0.2% |
| Mentions this run | 51 | 1 |
| Positive in AI answers | 35% | 50% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Databricks 0pp · Langfuse 0pp over 0 weekly runs.
Engine by engine
Databricks leads on 3 of 3 engines
Head to head in AI answers
1 engine answers name both brands
| Prompt | Engine | Databricks | Langfuse |
|---|---|---|---|
| Top MLOps platform options for B2B SaaS companies | AI Mode | #1 | #10 |
Features, pricing & fit
| Dimension | Databricks | Langfuse |
|---|---|---|
| Pricing model | — | Usage-based |
| Entry price | — | Free; paid from $29 / mo |
| Free plan | — | Yes |
| Deployment | Available across all major cloud providers | Langfuse Cloud in US, EU, Japan and HIPAA regions, or self-hosted under the MIT license |
| Integrations | — | 100+ |
| Compliance | ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3 | SOC 2 Type II, ISO 27001, HIPAA-ready region, GDPR |
| Support | Technical support on request, Technical documentation | Community support via GitHub, In-app support, Private Slack or MS Teams channel on Pro and Enterprise plans, Named lead support engineer on Enterprise plans |
| Founded | 2013 | — |
| Headquarters | San Francisco, CA | — |
| Employees | 5,000+ | — |
| Funding | Round at $60B valuation, including secondary sale | Seed · $4M raised |
| Best for | Data engineering, data science, analytics and AI teams at startups and global enterprises | Engineering teams building LLM applications and AI agents that want open-source, self-hostable tracing and evaluation |
Plans side by side
Databricks
Pricing not available.
Pros and cons
Themes from the AI answers that mention each brand
Databricks
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
- Top customer satisfaction ratings alongside Snowflake
- Free trial and free Edition for learning
- Discounts for annual prepaid commitments
- Complex consumption-based pricing with no single fixed price
- Best only when ML, Spark, or Python skills are central to the team
Langfuse
- Discounted cloud pricing for qualifying early-stage startups
- Well suited to evaluating and debugging LLM or agent behavior
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Databricks vs Langfuse”, https://slateindex.ai/compare/databricks-vs-langfuse, data of Nov 2, 2026. Licence: CC BY 4.0.