Apache SparkOpen-source multi-language engine for data engineering, data science and machine learning.
vs
ClickHouseThe leading database for AI
Comparison · Data Warehouse · weekly run Nov 3
Apache Spark vs ClickHouse
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
ClickHouse is the stronger AI pick in Data Warehouse: it has a visibility score of 16.5 versus 0.9 for Apache Spark.
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 ClickHouse if…
- You want the brand AI engines rank higher (16.5 vs 0.9)
- You need HIPAA or PCI coverage
- fast real-time analytics
- high-concurrency analytics performance
AI visibility side by side
Latest weekly run · Nov 3
| Metric | Apache Spark | ClickHouse |
|---|---|---|
| Visibility score | 0.9% | 16.5% |
| Change vs last week | New | New |
| Rank in Data Warehouse | #26 | #8 |
| Share of voice | 0.5% | 5.4% |
| Mentions this run | 3 | 30 |
| Positive in AI answers | — | 58% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Apache Spark 0pp · ClickHouse 0pp over 0 weekly runs.
Engine by engine
ClickHouse leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
Apache SparkClickHouse
Head to head in AI answers
0 engine answers name both brands
0Apache Spark ranked higher
0ClickHouse ranked higher
Features, pricing & fit
| Dimension | Apache Spark | ClickHouse |
|---|---|---|
| Pricing model | — | Usage-based |
| Entry price | — | $0.218 / mo |
| Free plan | — | No · 30-day trial |
| Deployment | Runs on single machines or on clusters: standalone, Hadoop YARN, Apache Mesos or Kubernetes. | ClickHouse Cloud on AWS, GCP and Azure, self-managed open-source installs, and Bring Your Own Cloud within the customer's own VPC. |
| Integrations | — | 100+ |
| Compliance | — | HIPAA, PCI |
| Support | — | Expert support with 1 business day response time on Basic, Expert support with 1 hour response time on Scale, Enterprise support with 30 min response time for Severity 1 issues, Named Lead Support Engineer on Enterprise |
| Founded | 2010 | 2009 |
| Headquarters | Wilmington, Delaware | Palo Alto, CA, United States |
| Employees | 5,000+ | 501–1,000 |
| Funding | — | Series D, led by Dragoneer |
| Best for | Data engineering, data science and machine learning work on single machines or clusters. | Developers and data teams that need real-time queries on large datasets at an affordable cost, including teams adding a speed layer on top of an existing data warehouse or OLTP database. |
Plans side by side
Apache Spark
Pricing not available.
ClickHouse
Basic$0.218per compute unit / hr
Scale$0.299per compute unit / hr
Enterprise$0.39per compute unit / hr
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
ClickHouse
- fast real-time analytics
- high-concurrency analytics performance
- strong for observability and log analytics
- $300 credits and 30-day trial
- best raw performance-to-cost ratio
- self-hosting requires scaling and maintenance work
- efficient operation at very large scale needs specialized expertise
- specialist option rather than broad enterprise warehouse replacement
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Apache Spark vs ClickHouse”, https://slateindex.ai/compare/apache-spark-vs-clickhouse, data of Nov 3, 2026. Licence: CC BY 4.0.