# ClickHouse AI visibility in Databases & Data Infrastructure Canonical: https://devtune.ai/verticals/databases-data-infrastructure/clickhouse [Website](https://clickhouse.com/) Updated: 2026-10-18T18:51:18.525881+00:00 Prompts: 25 Runs: 6 ## Platforms - perplexity - google-ai-mode - bing-copilot-search - chatgpt-search - google-ai - xai-search Rank: 8 Total brands: 15 Measured responses: 150 Presence percent: 3.3333333333333335 Share of voice percent: 5.434782608695652 Average position: 5.9 Docs presence percent: 0.6666666666666667 Blog presence percent: 0.6666666666666667 Brand mention percent: 10.666666666666668 ## Profile 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. Product summary: 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 capabilities - 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 ### Target users - Data engineers building real-time analytics pipelines - Platform and backend engineers embedding analytics into products - Data analysts and BI teams querying large-scale datasets - DevOps and SRE teams managing log and observability infrastructure - ML and AI engineers powering model training and inference analytics - Enterprise data teams running cloud data warehouses ### Key use cases - 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 Integrations ecosystem: ClickHouse offers 100+ integrations across data ingestion, visualization, language clients, and orchestration. ClickPipes—the managed connector service—supports Kafka, AWS Kinesis, S3, Postgres CDC, MySQL CDC, MongoDB, BigQuery, and DynamoDB. Native language clients cover Python, Go, Java, JavaScript, Rust, C++, and C#. Visualization integrations include Grafana, Tableau, Metabase, and Apache Superset. Data pipeline integrations include dbt, Airbyte, and Fivetran. ClickHouse Cloud is available natively on AWS, GCP, and Azure marketplaces, and supports JDBC/ODBC for broad compatibility. Pricing summary: 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. Review summary: 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. Competitive positioning: 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. 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. ### Source urls - https://clickhouse.com/company/our-story - https://clickhouse.com/pricing - https://github.com/ClickHouse/ClickHouse - https://clickhouse.com/docs/integrations - https://sacra.com/c/clickhouse/ - https://www.bloomberg.com/news/articles/2026-01-16/clickhouse-lands-15-billion-valuation-in-ai-database-race - https://www.bloomberg.com/news/articles/2025-05-29/khosla-led-deal-values-data-startup-clickhouse-at-6-35-billion - https://www.gartner.com/reviews/product/clickhouse-cloud - https://www.peerspot.com/products/clickhouse-reviews - https://clickhouse.com/user-stories - https://clickhouse.com/blog/mintlify - https://clickhouse.com/blog/longbridge-technology-simplifies-their-architecture-and-achieves-10x-performance-boost-with-clickhouse Reviewed at: 2026-04-28T23:22:21.529+00:00 ### Customer outcomes | Customer | Summary | Metric | | --- | --- | --- | | Mintlify | 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. | 60% lower cost; dashboard latency reduced to <1 second; ~30% NPS improvement | | Longbridge Technology | 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. | 10x query performance; 4x cost reduction; 300% query efficiency improvement | | SolarWinds | 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. | 60% reduction in query times; 300M messages/second | | Character.AI | 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. | 50% lower observability cost; 10x log volume handled | | Cloudflare | 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. | 6M+ HTTP requests/second; queries return in <2 seconds at quadrillion-row scale | ### Reviews breakdown | Platform | Score | Score max | Review count | Url | | --- | --- | --- | --- | --- | | Gartner Peer Insights | 4.5 | 5 | 31 | https://www.gartner.com/reviews/product/clickhouse-cloud | ### Review themes #### 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 ### Company facts Founded year: 2009 Hq: Bay Area, CA, USA #### Founders - Aaron Katz - Alexey Milovidov - Yury Izrailevsky Employees range: 400-500 Total funding: $1.05B+ Valuation: ~$15B Arr: Not available Customer count: 100k+ developers Status: Private Readiness: Not available ## Ranking | Display name | Pair count | Total pairs | Presence percent | Avg position | | --- | --- | --- | --- | --- | | Neon | 13 | 150 | 8.666666666666668 | 5.310344827586207 | | Supabase | 13 | 150 | 8.666666666666668 | 9.76923076923077 | | PlanetScale | 12 | 150 | 8 | 6.851851851851852 | | CockroachDB | 12 | 150 | 8 | 7.421052631578948 | | MongoDB | 9 | 150 | 6 | 4.0588235294117645 | | PingCAP | 9 | 150 | 6 | 6.3076923076923075 | | QuestDB | 6 | 150 | 4 | 7.833333333333333 | | ClickHouse | 5 | 150 | 3.3333333333333335 | 5.9 | | Redis | 2 | 150 | 1.3333333333333335 | 2 | | SingleStore | 2 | 150 | 1.3333333333333335 | 4 | | Timescale | 2 | 150 | 1.3333333333333335 | 5 | | Turso | 2 | 150 | 1.3333333333333335 | 5 | | Xata | 1 | 150 | 0.6666666666666667 | 4 | | Fauna | 0 | 150 | 0 | Not available | | Gel | 0 | 150 | 0 | Not available | ## Platform breakdown | Platform | Prompt count | Presence rate | | --- | --- | --- | | perplexity | 2 | 8 | | google-ai-mode | 1 | 4 | | bing-copilot-search | 0 | 0 | | chatgpt-search | 2 | 8 | | google-ai | 0 | 0 | | xai-search | 0 | 0 | ## Strengths | Prompt text | Platform count | Avg position | | --- | --- | --- | | Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods? | 2 | 1 | | Which serverless database platforms maintain the best read/write throughput under sustained load with reliable autoscaling? | 1 | 6 | ## Gaps | Prompt text | Competitor presence count | | --- | --- | | Which developer-focused database platforms integrate best with IaC tools so database provisioning and config can be version-controlled? | 3 | | Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store? | 3 | | Which managed database platforms make multi-cloud portability practical — so moving between cloud providers isn't a nightmare? | 3 | | Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change? | 3 | | Which developer-focused database platforms handle schema migrations with CI/CD pipeline tooling out of the box? | 3 | ## Topic scores | Topic name | Prompt count | Cited prompt count | | --- | --- | --- | | Capability | 5 | 1 | | Developer Experience | 5 | 0 | | Integrations & Ecosystem | 5 | 0 | | Performance & Reliability | 5 | 2 | | Setup & First Run | 5 | 0 | ## Prompt results - Prompt text: What are the best dedicated vector databases, and how do they compare to adding vector search extensions to an existing relational database? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | PlanetScale | 4 | ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: What tools sync data from a primary operational database to an analytics warehouse for real-time reporting without heavy ETL infrastructure? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: Which managed database platforms offer the best multi-region replication with automatic conflict resolution for write-write scenarios? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | CockroachDB | 19 | ##### Google-ai ##### Xai-search - Prompt text: Which developer-focused database platforms integrate best with IaC tools so database provisioning and config can be version-controlled? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | MongoDB | 1 | | CockroachDB | 3 | | Neon | 4 | | PlanetScale | 6 | ##### Google-ai-mode | Display name | Position | | --- | --- | | Supabase | 1 | | MongoDB | 5 | | PlanetScale | 8 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | MongoDB | 1 | | Neon | 3 | | CockroachDB | 6 | | PlanetScale | 8 | ##### Google-ai ##### Xai-search - Prompt text: What tools and benchmarks help compare database platforms for high-concurrency transactional workloads before committing to one? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: Which cloud database platforms support change data capture for streaming row-level changes to a message queue or event bus with low latency? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: Which developer-focused databases offer the best local development experience that actually mirrors the production setup? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 3 | ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Neon | 10 | | Supabase | 13 | | MongoDB | 33 | ##### Google-ai ##### Xai-search - Prompt text: What's the fastest serverless relational database to spin up and connect to a Node.js backend for a new SaaS app? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | Turso | 3 | | Supabase | 5 | ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 4 | | Turso | 6 | ##### Google-ai ##### Xai-search - Prompt text: Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods? #### Brand position by platform Perplexity: Not available Google-ai-mode: 1 Bing-copilot-search: Not available Chatgpt-search: 1 Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | Timescale | 4 | ##### Google-ai-mode | Display name | Position | | --- | --- | | ClickHouse | 1 | | QuestDB | 2 | ##### Bing-copilot-search | Display name | Position | | --- | --- | | QuestDB | 2 | ##### Chatgpt-search | Display name | Position | | --- | --- | | ClickHouse | 1 | | QuestDB | 6 | ##### Google-ai ##### Xai-search - Prompt text: Which globally distributed SQL databases are worth evaluating for a latency-sensitive SaaS product compared to a traditional single-region setup? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | PlanetScale | 7 | ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | CockroachDB | 9 | | PingCAP | 15 | ##### Google-ai ##### Xai-search - Prompt text: Which managed database services offer the best backup and point-in-time recovery for production applications handling financial transactions? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store? #### Brand position by platform Perplexity: 6 Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: 8 Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | PingCAP | 1 | | SingleStore | 3 | | ClickHouse | 6 | ##### Google-ai-mode | Display name | Position | | --- | --- | | PingCAP | 2 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | SingleStore | 1 | | PingCAP | 2 | | ClickHouse | 8 | ##### Google-ai ##### Xai-search - Prompt text: Which managed database platforms have the best ORM and query builder compatibility for JavaScript and Python ecosystems? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 5 | ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: Which ORMs and query builders offer the best TypeScript experience for a distributed SQL database? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | CockroachDB | 5 | ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: Which managed database platforms make multi-cloud portability practical — so moving between cloud providers isn't a nightmare? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | MongoDB | 1 | | CockroachDB | 4 | ##### Google-ai-mode | Display name | Position | | --- | --- | | CockroachDB | 3 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | CockroachDB | 1 | | MongoDB | 3 | ##### Google-ai ##### Xai-search - Prompt text: Which document databases handle schema evolution most smoothly — without requiring migration scripts for every change? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | MongoDB | 1 | ##### Google-ai-mode | Display name | Position | | --- | --- | | MongoDB | 1 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | MongoDB | 1 | ##### Google-ai ##### Xai-search - Prompt text: I'm evaluating managed cloud databases versus self-hosted options for a seed-stage product — what should I look at? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Supabase | 5 | ##### Google-ai ##### Xai-search - Prompt text: Which serverless database platforms maintain the best read/write throughput under sustained load with reliable autoscaling? #### Brand position by platform Perplexity: 6 Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | ClickHouse | 6 | ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: Which time-series databases have the best query authoring and debugging experience for teams coming from relational databases? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | QuestDB | 1 | ##### Google-ai-mode ##### Bing-copilot-search | Display name | Position | | --- | --- | | QuestDB | 5 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Timescale | 6 | | QuestDB | 15 | ##### Google-ai ##### Xai-search - Prompt text: Which cloud-native database platforms handle connection pooling best for serverless workloads with unpredictable connection spikes? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 8 | ##### Google-ai-mode | Display name | Position | | --- | --- | | Neon | 2 | | PlanetScale | 5 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Supabase | 6 | ##### Google-ai ##### Xai-search - Prompt text: Which developer-focused database platforms handle schema migrations with CI/CD pipeline tooling out of the box? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | PlanetScale | 1 | | Neon | 4 | ##### Google-ai-mode | Display name | Position | | --- | --- | | Supabase | 2 | | PlanetScale | 4 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Supabase | 2 | | Neon | 11 | | PlanetScale | 13 | ##### Google-ai ##### Xai-search - Prompt text: What in-memory caching tools integrate best with persistent databases — and which are worth adding versus just optimizing primary database queries? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | Redis | 1 | ##### Google-ai-mode ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Redis | 2 | ##### Google-ai ##### Xai-search - Prompt text: Which distributed SQL platforms support migrating from a legacy relational database with minimal downtime for a production application? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | CockroachDB | 1 | | PingCAP | 5 | ##### Google-ai-mode | Display name | Position | | --- | --- | | CockroachDB | 3 | | PingCAP | 6 | ##### Bing-copilot-search ##### Chatgpt-search ##### Google-ai ##### Xai-search - Prompt text: Which database platforms support branching so I can get a fresh isolated database copy per pull request for feature development? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | Neon | 2 | | PlanetScale | 3 | ##### Google-ai-mode | Display name | Position | | --- | --- | | Xata | 1 | | Supabase | 4 | | PlanetScale | 8 | ##### Bing-copilot-search ##### Chatgpt-search | Display name | Position | | --- | --- | | Neon | 1 | | Supabase | 3 | | PlanetScale | 6 | ##### Google-ai ##### Xai-search - Prompt text: Which distributed SQL databases handle automatic failover most reliably when a node goes down — with the fastest recovery times? #### Brand position by platform Perplexity: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Chatgpt-search: Not available Google-ai: Not available Xai-search: Not available #### Platform rows ##### Perplexity | Display name | Position | | --- | --- | | CockroachDB | 3 | ##### Google-ai-mode | Display name | Position | | --- | --- | | CockroachDB | 3 | | PingCAP | 4 | ##### Bing-copilot-search | Display name | Position | | --- | --- | | PingCAP | 6 | ##### Chatgpt-search | Display name | Position | | --- | --- | | PingCAP | 9 | ##### Google-ai ##### Xai-search ## Top sources | Url | Title | Domain | Logo url | Source vertical | Content type | Citation count | Last30d count | | --- | --- | --- | --- | --- | --- | --- | --- | | https://clickhouse.com/resources/engineering/alloydb-alternatives | Best AlloyDB alternatives in 2026 for enterprise PostgreSQL ... | clickhouse.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/9a90dcfe-144c-484b-b3e8-1ad69eb3df89/1e29692de760c893495a61b45b2165c4205bbba3.png | commercial | listicle | 3 | 3 | | https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/use-cases/time-series/05_query-performance.md | clickhouse-docs/docs/use-cases/time-series/05_query-performance.md at main · ClickHouse/clickhouse-docs | github.com | Not available | commercial | documentation | 3 | 3 | | https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/best-practices/partitioning_keys.mdx | clickhouse-docs/docs/best-practices/partitioning_keys.mdx at main · ClickHouse/clickhouse-docs | github.com | Not available | commercial | documentation | 2 | 2 | | https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/managing-data/updating-data/overview.mdx | clickhouse-docs/docs/managing-data/updating-data/overview.mdx at main · ClickHouse/clickhouse-docs | github.com | Not available | commercial | documentation | 2 | 2 | | https://clickhouse.com/docs/get-started/use-cases/real-time-analytics | clickhouse.com · docs · get-startedReal-time analytics - ClickHouse Documentation | clickhouse.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/9a90dcfe-144c-484b-b3e8-1ad69eb3df89/1e29692de760c893495a61b45b2165c4205bbba3.png | commercial | documentation | 1 | 1 | | https://clickhouse.com/docs/get-started/migrate/postgres/overview | clickhouse.com › docs › get-startedComparing PostgreSQL and ClickHouse - ClickHouse Documentation | clickhouse.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/9a90dcfe-144c-484b-b3e8-1ad69eb3df89/1e29692de760c893495a61b45b2165c4205bbba3.png | commercial | documentation | 1 | 1 | | https://clickhouse.com/blog/netflix-petabyte-scale-logging | How Netflix optimized its petabyte-scale logging system with ... | clickhouse.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/9a90dcfe-144c-484b-b3e8-1ad69eb3df89/1e29692de760c893495a61b45b2165c4205bbba3.png | commercial | blog_post | 1 | 1 | ## Response excerpts | Prompt text | Platform | Excerpt | | --- | --- | --- | | What tools and benchmarks help compare database platforms for high-concurrency transactional workloads before committing to one? | bing-copilot-search | Concurrency, Data & Nodes Tested](https://www.exasol.com/blog/exasol-vs-clickhouse-vs-starrocks-vs-trino-vs-duckdb/) * Hardware realism: Run benchmarks on infrastructure similar to your production environment (cloud benchmarks often overstate per... | | Which time-series databases maintain query performance best at 10 million events per second ingestion over long retention periods? | bing-copilot-search | For sustained query performance at extreme ingestion rates (≈10M events/sec) with long retention, the strongest candidates are QuestDB, ClickHouse, and InfluxDB 3.0, with TimescaleDB viable when SQL compatibility is critical. | | Which columnar databases handle mixed OLAP and OLTP workloads well — when does it make sense to use one over a standard row-store? | bing-copilot-search | ## 📊 Columnar Databases That Handle Mixed Workloads * ClickHouse * Extremely fast for analytical queries (aggregations, scans over billions of rows). | ## Competitor excerpts | Platform | Competitor name | Excerpt | | --- | --- | --- | | perplexity | MongoDB | ...database provisioning and configuration, these platforms stand out: \| Platform \| IaC fit \| Best for \| \|---\|---\|---\| \| MongoDB Atlas \| Strongest overall: an official, HashiCorp-verified Terraform provider covers a broad range of Atlas resources, i... | | perplexity | CockroachDB | \| \| CockroachDB Cloud \| Strong: its Terraform provider can provision and manage clusters and related resources. | | google-ai-mode | Supabase | Terraform provider \| Supabase FeaturesNeon Provider \| Pulumi Registry[Docs overview \| supabase/supabase \| Terraform \| Terraform Registry](https://regis... | | chatgpt-search | MongoDB | My top recommendation is MongoDB Atlas for the most mature database-specific Terraform integration, Neon for developer-centric PostgreSQL workflows, and CockroachDB Cloud or PlanetScale for teams that want managed databases with programmable infrastructure. | | chatgpt-search | Neon | My top recommendation is MongoDB Atlas for the most mature database-specific Terraform integration, Neon for developer-centric PostgreSQL workflows, and CockroachDB Cloud or PlanetScale for teams that want managed databases with programmable infrastructure. | | perplexity | SingleStore | \| \| SingleStore \| Offers in-memory rowstore tables for demanding point-lookup and update-heavy transactions, plus on-disk columnstore/“Universal Storage” with features such as indexes, row-level locking, and upserts for mixed workloads. | | google-ai-mode | PingCAP | pingcap.com/article/tidb-the-ultimate-htap-database-for-modern-applications/) * * OLTP needs fast single-row lookups, heavy concurrent writes, and strict ACID guarantees (traditionally best on row-stores like PostgreSQL or MySQL). | | chatgpt-search | SingleStore | ## 2. SingleStore Best for mixed application SQL and real-time analytics Combines rowstore and columnstore table options in a distributed SQL database. | | chatgpt-search | PingCAP | pingcap.com/tidb/stable/tiflash-overview/)Primary Key tableData Update and Delete ## 3. When does a columnar database beat a standard row-store? | | perplexity | MongoDB | \| Platform \| Why it can help \| Important caveat \| \|---\|---\|---\| \| MongoDB Atlas \| Runs on AWS, Azure, and Google Cloud. | | google-ai-mode | CockroachDB | ...n how they abstract infrastructure: * * Distributed SQL Databases (Cloud-Agnostic & Native Multi-Cloud) * _CockroachDB Dedicated / BYOC_ : Built on a shared-nothing, distributed architecture, _ CockroachDB_ abstracts underlying cloud st... | | chatgpt-search | CockroachDB | My shortlist would start with CockroachDB, MongoDB Atlas, YugabyteDB, Google Cloud AlloyDB Omni, and cloud-neutral PostgreSQL or MySQL deployments. | ## Trend Visibility delta: -3.2727272727272725 Avg position delta: 2.3000000000000003 Citation count delta: 5