AI visibility report
AI visibility report for ClickHouse in Databases & Data Infrastructure.
Outside the top three on 21 of the 25 prompts buyers actually ask.
PlanetScale is cited on 6 of those losses.
Free trial. Setup comes pre-filled for ClickHouse.
Track ClickHouse across these prompts daily.
Start free trialStill absent from 97.3% of tracked prompt responses
Top-3 citations across 150 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
ChatGPT
Gemini Search
Google AI Mode
Perplexity
Bing Copilot
GrokHow to read this. ClickHouse appears in 2.7% of tracked prompt responses. Presence is absolute coverage; share of voice is relative citation share; sentiment measures tone only when the brand appears.
Where ClickHouse is losing
Prompts where competitors are visible and ClickHouse is not.
These prompt-level losses are the first prompts to track and repair.
Where ClickHouse is winning
No clear strengths identified yet.
Where ClickHouse is losing5
Which distributed SQL platforms support migrating from a legacy relational database with minimal downtime for a production application?
Competitors on 4 platforms
Track this promptWhich document databases handle schema evolution most smoothly — without requiring migration scripts for every change?
Competitors on 4 platforms
Track this promptWhich time-series databases have the best query authoring and debugging experience for teams coming from relational databases?
Competitors on 3 platforms
Track this promptWhich distributed SQL databases handle automatic failover most reliably when a node goes down — with the fastest recovery times?
Competitors on 3 platforms
Track this promptWhich database platforms support branching so I can get a fresh isolated database copy per pull request for feature development?
Competitors on 3 platforms
Track this prompt
Track ClickHouse daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
ClickHouse is an open-source, column-oriented OLAP database management system designed for real-time analytics at massive scale. Originally developed at Yandex beginning in 2009 and open-sourced in 2016 under Apache 2.0, it was commercialized by ClickHouse, Inc.—incorporated in Delaware in 2021. The platform uses columnar storage, vectorized query execution, and advanced compression to deliver sub-second query performance across billions to trillions of rows. It is available as a free self-managed distribution or as ClickHouse Cloud, a fully managed, consumption-based service on AWS, GCP, and Azure. Core use cases include real-time analytics, observability (logs, metrics, traces), data warehousing, ML/GenAI infrastructure, and financial data platforms. Notable customers include Cloudflare, Lyft, Tesla, Anthropic, Meta, Spotify, GitLab, and Sony.
ClickHouse is a high-performance, open-source column-oriented OLAP database for real-time SQL analytics on large-scale datasets, offered as a self-managed open-source distribution or as a fully managed cloud service (ClickHouse Cloud) on AWS, GCP, and Azure, with additional products including ClickStack (open-source observability), chDB (in-process SQL engine), and Langfuse (LLM observability, acquired January 2026).
Key Facts
- Founded
- 2009
- HQ
- Bay Area, CA, USA
- Founders
- Aaron Katz, Alexey Milovidov, Yury Izrailevsky
- Employees
- 400-500
- Funding
- $1.05B+
- Customers
- 100k+ developers
- Valuation
- ~$15B
- Status
- Private
Target users
Key Capabilities10
- Columnar storage engine (MergeTree family) for high-speed OLAP queries
- Vectorized query execution maximizing CPU parallelism across all cores
- Real-time data ingestion at billions of rows per day
- Petabyte-scale horizontal sharding and replication
- Materialized views and pre-aggregated rollups for sub-second dashboards
- Compute-storage separation via SharedMergeTree on ClickHouse Cloud
- Vector search support for ML/AI and GenAI applications
- ClickPipes managed connectors for streaming and CDC ingestion
- Open-source under Apache 2.0 with self-managed and fully managed cloud options
- 100+ integrations with BI, ETL, observability, and AI tooling
Key Use Cases7
- Real-time analytics dashboards at petabyte scale
- Log, metric, and trace storage and querying (observability)
- Cloud data warehousing and ad-hoc analytical exploration
- ML and GenAI data infrastructure with vector search
- Financial market data storage and real-time trade analytics
- Fraud detection and cybersecurity event analytics
- User-facing embedded analytics products
ClickHouse customer outcomes
60% lower cost; dashboard latency reduced to <1 second; ~30% NPS improvement
Replaced PostHog with ClickHouse Cloud for real-time analytics dashboards. Dashboard load times dropped from tens of seconds to sub-one-second, driving an estimated 30% NPS improvement, at 60% lower cost with zero ongoing maintenance.
10x query performance; 4x cost reduction; 300% query efficiency improvement
Migrated market data storage from a complex PostgreSQL/Redis/DynamoDB stack to ClickHouse, consolidating architecture and achieving a 10x improvement in query performance, 4x cost reduction, and 300% improvement in query efficiency.
60% reduction in query times; 300M messages/second
Used ClickHouse to power real-time observability for 300,000+ customers, processing 300 million messages per second with a 60% reduction in query times and optimized memory usage.
50% lower observability cost; 10x log volume handled
Deployed ClickStack for GPU observability at scale, handling 10x more log volume than the prior solution at 50% lower cost, with query latency dropping from 1–2 minutes to near-instant.
6M+ HTTP requests/second; queries return in <2 seconds at quadrillion-row scale
Runs open-source ClickHouse across 20+ clusters for internal analytics, bot management, and customer dashboards, processing 6M+ HTTP requests per second at quadrillion-row scale with sub-two-second query results.
Recent Trend
How AI describes ClickHouse3
ClickHouse (via Official Docker Images & ClickHouse Local) * The Analytics Powerhouse: For columnar, high-performance analytical databases, ClickHouse solves the historical pain of running heavy analytics engines on a laptop.
Which developer-focused databases offer the best local development experience that actually mirrors the production setup?
ClickHouse (High-Performance Columnar OLAP) While technically a columnar database management system rather than a strictly traditional TSDB, ClickHouse is widely adopted for massive-scale time-series, log, and event workloads.
Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods?
ResearchGate Traditional columnar databases (like ClickHouse or Snowflake) are built strictly for analytics and struggle with heavy, high-frequency writes or individual row updates.
Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store?
Most cited sources8
7What Is a Time-Series Database? Examples, Use Cases & ClickHouse Guide | Engineering | ClickHouse Resource Hub
clickhouse.com·Article
- 5
OLTP vs OLAP | Engineering | ClickHouse Resource Hub | ClickHouse
clickhouse.com·Article
- 4
Unifying OLTP and OLAP: HTAP databases, zero-ETL, and best-of-breed architectures | Engineering | ClickHouse Resource Hub
clickhouse.com·Article
- 3
When should you use a columnar database?
clickhouse.com·Article
- 3
What is a columnar database? Column stores explained | Engineering | ClickHouse Resource Hub
clickhouse.com·Article
- 1
The definitive guide to ClickHouse query optimization (2026) | Engineering | ClickHouse Resource Hub
clickhouse.com·Article
Alternatives in Databases & Data Infrastructure6
ClickHouse positions itself as the fastest and most resource-efficient real-time OLAP database, competing primarily on query speed, compression efficiency, and cost-per-query against cloud data warehouses (Snowflake, BigQuery, Redshift) and real-time analytics databases (SingleStore, QuestDB, Timescale).
- It differentiates via its open-source roots (Apache 2.0), a broad integration ecosystem (100+ connectors), and a fully managed cloud offering.
- The brand emphasizes that it is purpose-built for analytical workloads rather than a general-purpose database, making it the preferred 'speed layer' and OLAP engine for high-volume, low-latency data applications, with increasing focus on AI/ML and agent-facing database infrastructure.
Reviews
Praised
- Blazing-fast query performance on large datasets
- Efficient columnar storage and compression ratios
- Cost-effectiveness vs. traditional data warehouses
- Strong SQL compatibility and familiar query interface
- Powerful materialized views for real-time pre-aggregations
- Active open-source community and thorough documentation
- Smooth integrations with Grafana, dbt, and Kafka
- Reliable horizontal scalability for petabyte-scale workloads
Criticized
- Unsuitable for OLTP or mutation-heavy update/delete workloads
- Steep learning curve for schema and primary key design
- Asynchronous mutations are complex and resource-intensive
- Complex multi-table JOIN performance can lag row-oriented databases
- Self-managed cluster setup requires significant operational expertise
- Limited autoscaling granularity controls in ClickHouse Cloud
- Sparse pool of ClickHouse-experienced developers in the job market
- Some non-standard SQL behaviors and missing window functions
Users consistently praise ClickHouse for exceptional query speed on large datasets, efficient columnar storage and compression, strong cost-effectiveness relative to alternatives, and familiar SQL compatibility. Reviewers highlight particular strength in real-time analytics and observability workloads. Common criticisms center on the steep learning curve for optimal schema and primary key design, complexity of self-managed deployments, unsuitability for OLTP or mutation-heavy workloads, and some gaps in window function support. Gartner Peer Insights users rate it 4.5/5 across 31 reviews; PeerSpot users give it 8.6/10.
Pricing
Open-source ClickHouse is free to download and self-manage (Apache 2.0). ClickHouse Cloud uses a consumption-based pricing model: charges are based on compute and storage consumed, with automatic scaling and scale-to-zero when idle to minimize cost. Cloud pricing starts at approximately $50/month for entry-level usage. Enterprise Bring Your Own Cloud (BYOC) and ClickHouse Enterprise Edition pricing are available via custom contracts. AWS, GCP, and Azure Marketplace billing is supported.
Limitations
- ClickHouse is purpose-built for OLAP and is unsuitable for OLTP or transactional workloads.
- It lacks full ACID compliance for multi-statement transactions and does not efficiently support row-level updates or deletes—mutations are asynchronous, CPU-intensive background operations.
- Point lookups of individual rows are inefficient due to the sparse primary index.
- Complex multi-table JOINs can underperform compared to row-oriented databases.
- Schema and primary key design require careful upfront planning, creating a steep learning curve for new users.
- Self-managed cluster setup demands significant operational expertise.
- Autoscaling granularity on ClickHouse Cloud has been cited by some users as insufficiently configurable.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | ChatGPT | Google AI Mode | Gemini Search | Perplexity | Bing Copilot | Grok |
|---|---|---|---|---|---|---|
Capability1/5 cited (20%) | ||||||
Which managed database platforms offer the best multi-region replication with automatic conflict resolution for write-write scenarios? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What are the best dedicated vector databases, and how do they compare to adding vector search extensions to an existing relational database? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store? | Your brand and a competitor were cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which globally distributed SQL databases are worth evaluating for a latency-sensitive SaaS product compared to a traditional single-region setup? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What in-memory caching tools integrate best with persistent databases — and which are worth adding versus just optimizing primary database queries? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Developer Experience1/5 cited (20%) | ||||||
Which developer-focused databases offer the best local development experience that actually mirrors the production setup? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which ORMs and query builders offer the best TypeScript experience for a distributed SQL database? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change? | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Which time-series databases have the best query authoring and debugging experience for teams coming from relational databases? | Your brand and a competitor were cited | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which cloud-native database platforms handle connection pooling best for serverless workloads with unpredictable connection spikes? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Integrations & Ecosystem0/5 cited (0%) | ||||||
Which cloud database platforms support change data capture for streaming row-level changes to a message queue or event bus with low latency? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What tools sync data from a primary operational database to an analytics warehouse for real-time reporting without heavy ETL infrastructure? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which developer-focused database platforms integrate best with IaC tools so database provisioning and config can be version-controlled? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which managed database platforms have the best ORM and query builder compatibility for JavaScript and Python ecosystems? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which managed database platforms make multi-cloud portability practical — so moving between cloud providers isn't a nightmare? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Performance & Reliability1/5 cited (20%) | ||||||
Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods? | Your brand and a competitor were cited | A competitor was cited | Your brand was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which serverless database platforms maintain the best read/write throughput under sustained load with reliable autoscaling? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What tools and benchmarks help compare database platforms for high-concurrency transactional workloads before committing to one? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which managed database services offer the best backup and point-in-time recovery for production applications handling financial transactions? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which distributed SQL databases handle automatic failover most reliably when a node goes down — with the fastest recovery times? | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Setup & First Run0/5 cited (0%) | ||||||
What's the fastest serverless relational database to spin up and connect to a Node.js backend for a new SaaS app? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which distributed SQL platforms support migrating from a legacy relational database with minimal downtime for a production application? | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
I'm evaluating managed cloud databases versus self-hosted options for a seed-stage product — what should I look at? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which developer-focused database platforms handle schema migrations with CI/CD pipeline tooling out of the box? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which database platforms support branching so I can get a fresh isolated database copy per pull request for feature development? | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Turn this matrix into daily prompt monitoring.
Track prompt changesVertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | PingCAP | 8.0% | 15.8% | 2.0% | 2.7% | 6.7% | #4.8 | +0.49 |
| 2 | CockroachDB | 7.3% | 15.8% | 4.0% | 2.0% | 2.7% | #3.5 | +0.65 |
| 3 | Supabase | 5.3% | 10.0% | 5.3% | 0.0% | 21.3% | #3.8 | +0.64 |
| 4 | MongoDB | 4.7% | 9.2% | 3.3% | 0.0% | 19.3% | #3.3 | +0.53 |
| 5 | PlanetScale | 4.0% | 5.8% | 4.0% | 0.0% | 18.7% | #2.4 | +0.64 |
| 6 | QuestDB | 4.0% | 11.7% | 0.0% | 3.3% | 6.7% | #4.4 | +0.53 |
| 7 | Neon | 3.3% | 5.0% | 3.3% | 0.0% | 24.7% | #6.2 | +0.72 |
| 8 | Xata | 2.7% | 7.5% | 0.7% | 2.0% | 2.7% | #3.2 | +0.45 |
| 9 | Timescale | 2.7% | 5.8% | 1.3% | 1.3% | 2.0% | #3.4 | +0.55 |
| 10 | ClickHouse | 2.7% | 8.3% | 0.0% | 1.3% | 10.0% | #6.1 | +0.60 |
| 11 | Turso | 1.3% | 1.7% | 0.7% | 0.0% | 6.7% | #3.0 | +0.84 |
| 12 | Redis | 0.7% | 0.8% | 0.0% | 0.7% | 7.3% | #3.0 | +0.00 |
| 13 | SingleStore | 0.7% | 2.5% | 0.7% | 0.7% | 3.3% | #3.7 | +0.90 |
| 14 | Fauna | 0.0% | 0.0% | 0.0% | 0.0% | 0.7% | — | — |
| 15 | Gel | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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