ClickHouse

Connect an agent via an official MCP server G

Agent access

Drive the product through a documented public API G

Agent access

Delegate tasks to a built-in AI assistant inside the product G

Agentic features

Plug MCP servers into this product so it can use their tools G

Agent access

Download a machine-readable API spec (OpenAPI or equivalent) G

Api quality

Point an agent at llms.txt or agent-oriented docs G

Agent access

Use an official CLI G

Agent access

Run the product headlessly / in CI for automation G

Agent access

Operate the product with natural-language commands G

Agentic features

Get AI-generated insights and suggestions from my data inside the product G

Agentic features

Set up automations that run autonomously in the background G

Agentic features

Explore an interactive API reference with runnable examples G

Api quality

Rely on versioned APIs with a documented deprecation policy G

Api quality

Build against official SDKs G

Agent access

Issue scoped/least-privilege API credentials for an agent G

Agent access

Subscribe to events via webhooks G

Agent access

Test against a sandbox environment without touching production data G

Api quality

Run the same engine locally and keylessly — no account or cloud dependency — for offline development and CI tests G

Local loop

Create a ready-to-connect database in seconds through the CLI or API without capacity planning C

Provisioning

Idle databases scale to zero so prototypes and side projects cost nothing while the data stays durable C

Elasticity

Self-host the core product G

My coding agent can provision a database end to end — create it, fetch the connection string, apply schema, and run queries — through the API, CLI, or MCP without touching the dashboard C

Agent ops

Export all of my data in open formats and leave G

Published per-unit pricing for compute, storage, and traffic lets me predict my bill before committing G

Pricing

Define rules that trigger actions automatically on events G

I get real engine compatibility — the Postgres, MySQL, or SQLite dialect and extensions my existing code expects — not a lookalike subset C

Compatibility

Ship schema changes safely — online DDL, deploy requests, or branch-and-merge workflows — without locking or breaking production C

Migrations

Create an instant copy-on-write branch of my database — schema and data — to develop and test against production-shaped data C

Branching

Prevent my data from being used to train AI models G

Restore or branch the database to any point in time within the retention window to recover from bad writes C

Recovery

Run heavy analytical aggregations over large tables fast enough for dashboards without exporting to a separate warehouse C

Analytics

The official CLI covers my daily loop — create, connect, shell into, and inspect databases — without opening the dashboard C

Local loop

Compute autoscales up and down with load automatically, without manual resizes or downtime C

Elasticity

Perform bulk operations across many items at once G

Read the product's source under an open license G

Store embeddings and run vector similarity search natively without adding a separate vector database C

Ai data

A genuinely usable free tier lets me run real prototypes before paying G

Pricing

Do everything through the API that I can do in the UI G

An agent can run SQL and schema operations through scoped tools that distinguish read-only from destructive actions, so I can safely delegate database work C

Agent ops

Cheaply create thousands of isolated databases — one per agent, tenant, or preview — and manage the fleet programmatically C

Agent ops

Add read replicas and rely on documented high-availability and failover behavior C

Availability

Automatic backups run on a schedule I can see and configure, and restores are self-serve C

Recovery

See slow queries, index recommendations, and performance metrics in a built-in insights view C

Insights

Control data retention and deletion G

A built-in connection pooler handles thousands of concurrent connections without me operating my own pgbouncer or proxy C

Pooling

Choose where my data is stored (region/residency) G

Create and tear down per-pull-request database branches automatically from CI or my deploy platform C

Branching

Opt out of telemetry and usage tracking G

Place data or replicas in regions close to my users to keep read latency low worldwide C

Latency

Query over HTTP or WebSockets from serverless and edge functions with an official driver built for short-lived connections C

Drivers

Schedule recurring jobs or workflows G

The database works out of the box with my ORM and framework (Prisma, Drizzle, Django, Rails) with documented guides C

Integrations

Set spend caps or usage alerts so a runaway query or traffic spike cannot produce a surprise bill G

Cost controls

Import an existing production database with minimal downtime using a documented migration path C

Migrations

Reset a branch from its parent or restore it to an earlier state without rebuilding from a dump C

Branching

Version, review, and roll back my automations G