ClickHouse Data Types

ClickHouse can store various kinds of data in table cells. This section describes the supported data types and special considerations for using and/or implementing them if any.

note

You can check whether a data type name is case-sensitive in the system.data_type_families table.

ClickHouse data types include:

• Integer types: signed and unsigned integers (UInt8, UInt16, UInt32, UInt64, UInt128, UInt256, Int8, Int16, Int32, Int64, Int128, Int256)
• Floating-point numbers: floats(Float32 and Float64) and Decimal values
• Boolean: ClickHouse has a Boolean type
• Strings: String and FixedString
• Dates: use Date and Date32 for days, and DateTime and DateTime64 for instances in time
• JSON: the JSON object stores a JSON document in a single column
• UUID: a performant option for storing UUID values
• Low cardinality types: use an Enum when you have a handful of unique values, or use LowCardinality when you have up to 10,000 unique values of a column
• Arrays: any column can be defined as an Array of values
• Maps: use Map for storing key/value pairs
• Aggregation function types: use SimpleAggregateFunction and AggregateFunction for storing the intermediate status of aggregate function results
• Nested data structures: A Nested data structure is like a table inside a cell
• Tuples: A Tuple of elements, each having an individual type.
• Nullable: Nullable allows you to store a value as NULL when a value is "missing" (instead of the column settings its default value for the data type)
• IP addresses: use IPv4 and IPv6 to efficiently store IP addresses
• Geo types: for geographical data, including Point, Ring, Polygon and MultiPolygon
• Special data types: including Expression, Set, Nothing and Interval