Query Interface

Custom API SQL

ClickHouses provides two types of parsers: a full SQL parser and a data format parser. It uses SQL parser for all types of queries and the data format parser only for INSERT queries. Beyond the query language, it provides multiple user interfaces, including HTTP interface, JDBC driver, TCP interface, command-line client, etc.

Query Compilation

Code Generation

ClickHouse supports runtime code generation. The code is generated for every kind of query on the fly, removing all indirection and dynamic dispatch. Runtime code generation can be better when it fuses many operations together and fully utilizes CPU execution units.

Storage Architecture

Disk-oriented In-Memory

ClickHouse has multiple types of table engines. The type of the table engine determines where the data is stored, concurrent level, whether indexes are supported and some other properties. The table engines that store data on disks include TinyLog and Log. The Memory engine stores data in memory and this table engine is mainly used for temporary tables with external query data. The data of Memory engine will disapper after the server is restarted.

Concurrency Control

Not Supported

ClickHouse doesn't support transactions.

Stored Procedures

Not Supported

Currently, stored procedures and UDF are listed as open issues in ClickHouse.

Data Model

Column Family / Wide-Column

ClickHouse not only store data by columns, but also process data by columns.

System Architecture

Shared-Nothing

ClickHouse system is a cluster of shards. It uses asynchronous multimaster replication and there is no single point of contention across the system.

Query Execution

Vectorized Model

Views

Virtual Views Materialized Views

ClickHouse supports both virtual views and materialized views. The materialized views store data transformed by corresponding SELECT query. The SELECT query can contain DISTINCT, GROUP BY, ORDER BY, LIMIT, etc.

Storage Model

Decomposition Storage Model (Columnar)

ClickHouse is a column-oriented DBMS and it stores data by columns.

Joins

Hash Join

ClickHouse only supports hash join, which is done by placing right part of data in a hash table in memory. Hash join is faster but require enough memory.