Table support and schema¶

This topic covers the table types, data types, and schema capabilities supported by Snowpipe Streaming.

Apache Iceberg™ table support¶

Snowpipe Streaming supports ingestion into Snowflake-managed Apache Iceberg™ tables, including both Iceberg v2 and Iceberg v3 tables. For more information, see Snowpipe Streaming high-performance architecture with Apache Iceberg™ tables.

Schema evolution¶

Snowpipe Streaming supports automatic table schema evolution. When enabled, Snowflake can automatically add new columns that are detected in the incoming stream and drop NOT NULL constraints to accommodate new data patterns. For more information, see Table schema evolution.

Limitations of schema evolution:

Supported exclusively for standard Snowflake tables. External tables and Apache Iceberg™ tables aren’t supported.
The precision, scale, or length of existing columns can’t be increased automatically.
Schema evolution isn’t supported for structured data types. However, new columns that contain structured types are inferred as VARIANT.

Insert-only operations¶

The API is currently limited to inserting rows. To modify, delete, or combine data, write the “raw” records to one or more staging tables. Merge, join, or transform the data by using continuous data pipelines to insert modified data into destination reporting tables.

Supported Java data types¶

The following table summarizes which Java data types are supported for ingestion into Snowflake columns:


Snowflake column type	Allowed Java data type
CHAR VARCHAR	String primitive data types (int, boolean, char, …) BigInteger, BigDecimal
BINARY	byte[] String (hex-encoded)
NUMBER	numeric types (BigInteger, BigDecimal, byte, int, double, …) String
FLOAT	numeric types (BigInteger, BigDecimal, byte, int, double, …) String
BOOLEAN	boolean numeric types (BigInteger, BigDecimal, byte, int, double, …) String See boolean conversion details.
TIME	java.time.LocalTime java.time.OffsetTime String Integer-stored time `HH24:MI:SS.FFTZH:TZM` (for example, `20:57:01.123456789+07:00`) `HH24:MI:SS.FF` (for example, `20:57:01.123456789`) `HH24:MI:SS` (for example, `20:57:01`) `HH24:MI` (for example, `20:57`)
DATE	java.time.LocalDate java.time.LocalDateTime java.time.OffsetDateTime java.time.ZonedDateTime java.time.Instant String Integer-stored date `YYYY-MM-DD` (for example, `2013-04-28`) `YYYY-MM-DDTHH24:MI:SS.FFTZH:TZM` (for example, `2013-04-28T20:57:01.123456789+07:00`) `YYYY-MM-DDTHH24:MI:SS.FF` (for example, `2013-04-28T20:57:01.123456`) `YYYY-MM-DDTHH24:MI:SS` (for example, `2013-04-28T20:57:01`) `YYYY-MM-DDTHH24:MI` (for example, `2013-04-28T20:57`) `YYYY-MM-DDTHH24:MI:SSTZH:TZM` (for example, `2013-04-28T20:57:01-07:00`) `YYYY-MM-DDTHH24:MITZH:TZM` (for example, `2013-04-28T20:57-07:00`)
TIMESTAMP_NTZ TIMESTAMP_LTZ TIMESTAMP_TZ	java.time.LocalDate java.time.LocalDateTime java.time.OffsetDateTime java.time.ZonedDateTime java.time.Instant String Integer-stored timestamp `YYYY-MM-DD` (for example, `2013-04-28`) `YYYY-MM-DDTHH24:MI:SS.FFTZH:TZM` (for example, `2013-04-28T20:57:01.123456789+07:00`) `YYYY-MM-DDTHH24:MI:SS.FF` (for example, `2013-04-28T20:57:01.123456`) `YYYY-MM-DDTHH24:MI:SS` (for example, `2013-04-28T20:57:01`) `YYYY-MM-DDTHH24:MI` (for example, `2013-04-28T20:57`) `YYYY-MM-DDTHH24:MI:SSTZH:TZM` (for example, `2013-04-28T20:57:01-07:00`) `YYYY-MM-DDTHH24:MITZH:TZM` (for example, `2013-04-28T20:57-07:00`)
VARIANT ARRAY	String (must be a valid JSON) primitive data types and their arrays BigInteger, BigDecimal java.time.LocalTime java.time.OffsetTime java.time.LocalDate java.time.LocalDateTime java.time.OffsetDateTime java.time.ZonedDateTime java.util.Map<String, T> where T is a valid VARIANT type T[] where T is a valid VARIANT type List<T> where T is a valid VARIANT type
OBJECT	String (must be a valid JSON object) Map<String, T> where T is a valid variant type
GEOGRAPHY	Supported
GEOMETRY	Supported