ClickHouse vs Google BigQuery
Updated November 2026 · AppBreakup editorial
ClickHouse
An open-source column-oriented database for fast real-time analytics, with a managed cloud service.
Google BigQuery
Google Cloud's serverless data warehouse for SQL analytics, billed per query or by capacity.
The short answer
ClickHouse suits engineering teams building real-time dashboards, observability or product analytics over billions of rows, and it can be self-hosted at no licence cost. BigQuery suits teams on Google Cloud or GA4 who want a serverless warehouse with nothing to run. The biggest difference is control versus convenience: ClickHouse gives speed and hosting choice but asks more of you, BigQuery hides the infrastructure but ties you to Google Cloud.
ClickHouse or Google BigQuery: our take
ClickHouse is a column-oriented OLAP database focused on low-latency analytical SQL, used for product and web analytics, logs and traces, and reporting where queries need to return in milliseconds. BigQuery is Google Cloud's serverless data warehouse: you load data or point at files in cloud storage, run standard SQL, and Google allocates compute. BigQuery adds built-in machine learning in SQL, geospatial functions, streaming inserts and BigQuery Omni for querying data on AWS or Azure.
Deployment is where they differ most. ClickHouse is open source under Apache-2.0 and can be self-hosted on Linux, or run as ClickHouse Cloud on AWS, Google Cloud or Azure. BigQuery only runs on Google Cloud and has no self-hosted version. In exchange, BigQuery has no clusters to size or maintain, while ClickHouse needs care with schema and table-engine choices, and self-hosting a cluster takes real operational work. Updates, deletes and large joins are also weaker in ClickHouse than in general-purpose warehouses.
Pricing models suit different workloads. ClickHouse Cloud meters compute and storage separately, scales idle services to zero, and offers a 30-day trial with $300 credits. BigQuery's on-demand model charges $6.25 per TiB scanned, with the first 1 TiB per month free and the first 10 GiB of storage free, plus a capacity option for predictable spend. Careless queries over wide tables can make on-demand BigQuery bills climb.
Choose ClickHouse for live, user-facing dashboards and high-volume event or log data where speed and cost per query matter, and you have engineers to model the data. Choose BigQuery if you are on Google Cloud, work with GA4 exports, or want a warehouse without operations work.
Which should you pick?
Choose ClickHouse if…
- Engineering teams building real-time dashboards, observability or analytics over billions of rows
- You need Linux, macOS and Self-hosted, which Google BigQuery doesn't list
- Very fast aggregations over large tables, suited to live dashboards
- Apache 2.0 open source, so it can be self-hosted at no licence cost
Choose Google BigQuery if…
- Teams on Google Cloud or GA4 who want a warehouse with no servers to manage
- Fully serverless, with nothing to size or keep running
- Monthly free query and storage allowance for small projects
About each app
What is ClickHouse?
ClickHouse is a column-oriented OLAP database built for running analytical SQL queries over very large tables with low latency. Teams use it for product and web analytics, observability data such as logs and traces, and data-warehouse style reporting where queries need to come back in milliseconds rather than minutes. Its compression and vectorised execution make it cheap to store and scan billions of rows. The core database is open source under Apache 2.0 and can be self-hosted on Linux servers or run locally, so there is no licence cost if you operate it yourself. ClickHouse Inc. also sells ClickHouse Cloud, a managed service on AWS, Google Cloud and Azure that bills compute and storage separately and scales idle services to zero, with a trial that includes credits. Compared with Snowflake or BigQuery it is faster for real-time dashboards but asks more of you on data modelling, and joins and updates are less forgiving than in a traditional warehouse.
What is Google BigQuery?
BigQuery is Google Cloud's serverless data warehouse. There are no clusters or instances to set up: you load data or point it at files in cloud storage and run standard SQL, and Google allocates compute behind the scenes. It suits teams already on Google Cloud, marketers working with Google Analytics 4 exports, and anyone who wants a warehouse without operations work. It includes built-in machine learning in SQL (BigQuery ML), geospatial functions, streaming inserts, and BigQuery Omni for querying data held on AWS or Azure. Pricing has two compute models: on-demand, where you pay for the bytes each query scans with the first chunk each month free, and capacity pricing for predictable spend; storage is billed separately with a small free allowance. It only runs on Google Cloud, and careless queries over wide tables can scan a lot of data and cost more than expected.
Side by side
| Attribute | ClickHouse | Google BigQuery |
|---|---|---|
| Pricing | Open source | Free plan + paid |
| Open source | No | No |
| Self-hostable | No | No |
| Platforms | Web, Linux, macOS, Self-hosted | Web |
| Best for | Engineering teams building real-time dashboards, observability or analytics over billions of rows | Teams on Google Cloud or GA4 who want a warehouse with no servers to manage |
| Status | Active | Active |
ClickHouse vs Google BigQuery pricing
Platforms
| Platform | ClickHouse | Google BigQuery |
|---|---|---|
| Web | ||
| macOS | ||
| Linux | ||
| Self-hosted |
ClickHouse facts
5 of 5 verified- License
- Apache-2.0
- Checked Oct 29, 2026github.com(opens source in a new tab)
- “License: Apache-2.0 (Apache License 2.0).”
- Open source
- Yes
- Checked Oct 29, 2026clickhouse.com(opens source in a new tab)
- “Open source ClickHouse Fast open-source OLAP database for real-time analytics.”
- Free trial
- 30 days with $300 credits
- Checked Oct 29, 2026clickhouse.com(opens source in a new tab)
- “Start free with $300 in credits for 30 days.”
- Pricing model
- Compute and storage metered separately
- Checked Oct 29, 2026clickhouse.com(opens source in a new tab)
- “Pay only for the compute and storage you use, metered separately and scaled to zero when idle.”
- Cloud providers
- AWS, Google Cloud, Azure
- Checked Oct 29, 2026clickhouse.com(opens source in a new tab)
- “The best way to use ClickHouse. Available on AWS, GCP, and Azure.”
Google BigQuery facts
4 of 4 verified- Serverless
- Yes
- Checked Nov 1, 2026cloud.google.com(opens source in a new tab)
- “BigQuery is a serverless data analytics platform.”
- Free query allowance
- First 1 TiB per month
- Checked Nov 1, 2026cloud.google.com(opens source in a new tab)
- “The first 1 TiB per month is free.”
- Starting price
- $6.25 per TiB scanned (on-demand)
- Checked Nov 1, 2026cloud.google.com(opens source in a new tab)
- “$6.25 / 1 tebibyte, per 1 month / account The first 1 TiB per month is free.”
- Free storage
- First 10 GiB per month
- Checked Nov 1, 2026cloud.google.com(opens source in a new tab)
- “The first 10 GiB is free each month.”
Pros and cons of ClickHouse
- Very fast aggregations over large tables, suited to live dashboards
- Apache 2.0 open source, so it can be self-hosted at no licence cost
- Strong compression keeps storage costs down
- Managed cloud option on AWS, Google Cloud and Azure
- Schema and table-engine choices need care to get good performance
- Updates, deletes and large joins are weaker than in general-purpose warehouses
- Self-hosting a cluster takes real operational work
Pros and cons of Google BigQuery
- Fully serverless, with nothing to size or keep running
- Monthly free query and storage allowance for small projects
- Native exports from Google Analytics 4 and other Google products
- Machine learning models can be trained in plain SQL
- Tied to Google Cloud; there is no self-hosted version
- On-demand billing by data scanned can surprise teams that query wide tables
- Less control over performance tuning than with your own cluster
Other apps to consider
SnowflakeInstead of ClickHouse
A fully managed warehouse with less tuning to do, better for broad BI and data sharing than sub-second dashboards.
DatabricksInstead of ClickHouse
A lakehouse platform that adds Spark, notebooks and ML tooling on top of SQL analytics.
Tiger DataInstead of ClickHouse
Keeps analytics inside Postgres, so teams already on PostgreSQL avoid learning a new database.
ClickHouse vs Google BigQuery: common questions
Is ClickHouse better than Google BigQuery?
ClickHouse suits engineering teams building real-time dashboards, observability or product analytics over billions of rows, and it can be self-hosted at no licence cost. BigQuery suits teams on Google Cloud or GA4 who want a serverless warehouse with nothing to run. The biggest difference is control versus convenience: ClickHouse gives speed and hosting choice but asks more of you, BigQuery hides the infrastructure but ties you to Google Cloud.
Is ClickHouse free?
Yes. ClickHouse is free, open-source software.
Is Google BigQuery free?
Google BigQuery has a free plan, with paid plans for more features. See its verified pricing facts above for current limits.
Is ClickHouse or Google BigQuery open source?
Neither is open source.
Which platforms do ClickHouse and Google BigQuery support?
ClickHouse: Web, Linux, macOS and Self-hosted. Google BigQuery: Web.