Design and Manage ClickHouse Databases Visually with DbSchema

DbSchema lets you design, manage, and document ClickHouse databases. Create ER diagrams, define tables and columns, and generate SQL scripts - with or without a live database connection.

Use Git to share the design, compare it with the ClickHouse database, and deploy changes. DbSchema also includes a data editor, query builder, and HTML5 documentation - everything you need in one tool.

DbSchema Database Designer

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Visualizing ClickHouse Table Engines and Schema Topology

ClickHouse's MergeTree family of table engines — including ReplicatedMergeTree, SummingMergeTree, and AggregatingMergeTree — combined with ordering keys, partition expressions, and materialized views creates a schema topology that carries significant semantic weight beyond column definitions. DbSchema connects to ClickHouse and renders tables, materialized views, and their relationships as an ER diagram, helping engineers understand which materialized views aggregate which base tables, how partitioning is structured, and which tables are part of a replicated cluster. This visual layer makes it easier to reason about query routing and data freshness in complex analytical deployments.

Write and Execute Analytical SQL

DbSchema's SQL editor connects to ClickHouse via JDBC with syntax highlighting and result display in a tabular grid. Run aggregations, window functions, array operations, and ClickHouse-specific functions with immediate feedback — taking full advantage of ClickHouse's sub-second response times on large analytical datasets.

Writing and executing analytical SQL against ClickHouse in the DbSchema SQL editor

Build Queries Visually Without SQL

The visual query builder generates ClickHouse-compatible SQL from your table and column selections, letting analysts construct GROUP BY queries, apply WHERE filters, and join tables without writing SQL directly. This is particularly useful when onboarding analysts to a ClickHouse deployment for the first time.

DbSchema visual query builder generating ClickHouse analytical SQL queries

Explore Large ClickHouse Datasets Interactively

The data explorer fetches ClickHouse table rows with column filtering and pagination. Use it to inspect partition contents after ingestion, verify the output of materialized view refreshes, or sample rows from large MergeTree tables without writing a full query in the SQL editor.

Browsing ClickHouse table data with column filtering in the DbSchema data explorer

Connecting DbSchema to ClickHouse

ClickHouse exposes two ports by default: HTTP on 8123 and native TCP on 9000. The JDBC driver uses the HTTP interface. DbSchema can download the ClickHouse JDBC driver automatically on first connection. The JDBC URL format is jdbc:clickhouse://host:8123/dbname. For ClickHouse Cloud deployments, use the HTTPS endpoint on port 8443 and supply your service username and password. For self-hosted clusters requiring TLS, use the HTTPS URL and configure the appropriate certificate trust settings in the connection properties.

Why Teams Use DbSchema with ClickHouse

  • Visualize MergeTree table engines, ordering keys, and materialized view relationships as an ER diagram
  • Write and run ClickHouse SQL with syntax support from a desktop SQL editor
  • Explore large dataset contents and verify ingestion and materialization results interactively
  • Document the ClickHouse schema including materialized view topology for analytics team reference
  • Enable analysts to query ClickHouse data through a visual builder without learning the SQL dialect