Apache Spark vs Metabase
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Metabase is the stronger AI pick in Data Warehouse: it has a visibility score of 2 versus 0.9 for Apache Spark, and ranks ahead in 100% of the answers that name both.
Choose Apache Spark if…
- You prefer a larger, established vendor (5,000+ employees)
- Strong distributed processing capabilities for massive workloads
- Distributes query execution across a cluster of commodity machines
Choose Metabase if…
- You want the brand AI engines rank higher (2 vs 0.9)
- You need SOC 1 or SOC 2 Type II or GDPR or CCPA coverage
- Free open-source edition for self-hosting
- Easy to deploy and user-friendly
AI visibility side by side
Latest weekly run · Nov 3
| Metric | Apache Spark | Metabase |
|---|---|---|
| Visibility score | 0.9% | 2% |
| Change vs last week | New | New |
| Rank in Data Warehouse | #26 | #20 |
| Share of voice | 0.5% | 1.1% |
| Mentions this run | 3 | 6 |
| Positive in AI answers | — | 63% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Apache Spark 0pp · Metabase 0pp over 0 weekly runs.
Engine by engine
Metabase leads on 3 of 3 engines
Head to head in AI answers
1 engine answers name both brands
| Prompt | Engine | Apache Spark | Metabase |
|---|---|---|---|
| How do companies store and query business data at scale without a dedicated tool? | ChatGPT | #9 | #7 |
Features, pricing & fit
| Dimension | Apache Spark | Metabase |
|---|---|---|
| Pricing model | — | Per seat |
| Entry price | — | Free; paid from $100 per seat / mo |
| Free plan | — | Yes |
| Deployment | Runs on single machines or on clusters: standalone, Hadoop YARN, Apache Mesos or Kubernetes. | Self-hosted or Metabase Cloud, with air-gapped deployment available on Enterprise |
| Integrations | — | 237+ |
| Compliance | — | SOC 1, SOC 2 Type II, GDPR, CCPA |
| Support | — | Email, Support form, Slack, Microsoft Teams |
| Founded | 2010 | 2014 |
| Headquarters | Wilmington, Delaware | — |
| Employees | 5,000+ | 51–200 |
| Funding | — | Series B · $43M raised |
| Best for | Data engineering, data science and machine learning work on single machines or clusters. | Teams that want self-service analytics without relying on engineers, and software companies that need to embed analytics in their product |
Plans side by side
Apache Spark
Pricing not available.
Metabase
Pros and cons
Themes from the AI answers that mention each brand
Apache Spark
- Strong distributed processing capabilities for massive workloads
- Distributes query execution across a cluster of commodity machines
Metabase
- Free open-source edition for self-hosting
- Easy to deploy and user-friendly
- No-code visual builder and SQL for non-technical users
- Affordable, low-cost BI
- Best default starting point for startups and small teams
- Self-hosting means handling hosting, security, backups and updates yourself
- Extra token-based AI or custom usage fees on top of plans
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Apache Spark vs Metabase”, https://slateindex.ai/compare/apache-spark-vs-metabase, data of Nov 3, 2026. Licence: CC BY 4.0.