USER DOCUMENTATION
Data Types
Some components (especially extractors) store metadata about the table columns. For example, when a DB extractor
loads a table from the source database, it also records the physical column types from that table.
These are stored with each table column and can be used later on when working with the table. For
example, the transformation COPY mapping allows you to set data types for the tables inside
the transformations. Also, some writers, e.g., the Snowflake writer use
the table metadata to pre-fill the table columns configuration for you.
Even if a data type is available for a column, that column is always stored as text — keep this in mind especially in Transformations, where the output is always cast to text. The non-text column type is used only during a component (transformation or writer) execution. The basic idea behind this is that a text type has the best interoperability, so this averts many issues (e.g., some date values stored in a MySQL database might not be accepted by a Snowflake database and vice-versa).
Base Types
Data types from a source are mapped to a destination using a Base Type. The current base types are
STRING, INTEGER, NUMERIC, FLOAT, BOOLEAN,
DATE, and TIMESTAMP. This means that, for example, a MySQL extractor
may store the value BIGINT as a type of a column; that type maps to the INTEGER general type. When the Snowflake writer consumes this value, it will
read the general type INTEGER and choose a corresponding type for Snowflake, which happens to be also INTEGER.
This logic is again designed to ensure high interoperability between the components. See the conversion table below.
You view the extracted data types in the Storage Table detail:
You can also override the data type:
When you use the table (e.g. in Snowflake writer), you’ll see the data type you configured:
Note that the column type setting is in all cases only a metadata setting. It has no effect on the actual stored data. The data is converted only at the point of writing/copying (e.g to transformation or writer). That means that you can extract an integer column, mark it as timestamp in Storage and write it as integer into a target database (though you’ll be offered to write it as timestamp).
Through the corresponding API you access both the source and base type metadata.
Data Type Conversions
As described above, the source data type is converted to a base data type which is stored in metadata storage. The base type is then converted to the target data type. The following tables show mappings for each base type. The mapping
causes possible information loss (e.g. assigning SMALLINT to INTEGER). To minimize this, we also keep track of the data type
size and transfer that if possible. For example that a SMALLINT column would be stored as base type INTEGER with size 2. If the target database supports integer sizes, you will be offered to set the type in the target database as INTEGER(2).
STRING
Base type STRING represents any textual type - both CHARACTER VARYING (or VARCHAR) and TEXT types are included.
Also the string base type is used for any other unrecognized type on input. That means in the following table the
source type column is not an exhaustive list. It’s a list of reasonable string types which are converted to string, all
other unknown types are converted to string as well.
| Source | Source Type | Base Type | Target Type | Target |
|---|---|---|---|---|
| Generic | char | STRING | N/A | |
| character varying | ||||
| text | ||||
| varchar | ||||
| STRING | Hive | |||
| STRING | Impala | |||
| TEXT | MS SQL Server | |||
| MySQL | CHAR | VARCHAR | MySQL | |
| TEXT | ||||
| VARCHAR | ||||
| VARCHAR2 | Oracle | |||
| VARCHAR | PostgreSQL | |||
| Redshift | BPCHAR | VARCHAR | Redshift | |
| CHAR | ||||
| CHARACTER | ||||
| CHARACTER VARYING | ||||
| NCHAR | ||||
| NVARCHAR | ||||
| TEXT | ||||
| VARCHAR | ||||
| VARCHAR | SiSense | |||
| Snowflake | BINARY | VARCHAR | Snowflake | |
| CHAR | ||||
| CHARACTER | ||||
| STRING | ||||
| TEXT | ||||
| VARBINARY | ||||
| VARCHAR | ||||
| Synapse | BINARY | NVARCHAR | Synapse | |
| CHAR | ||||
| NCHAR | ||||
| NVARCHAR | ||||
| VARBINARY | ||||
| VARCHAR | ||||
| VARCHAR | Thoughtspot | |||
| Source | Source Type | Base Type | Target Type | Target |
INTEGER
The INTEGER base type represents data types for whole numbers.
| Source | Source Type | Base Type | Target Type | Target |
|---|---|---|---|---|
| Generic | bigint | INTEGER | ||
| bigserial | ||||
| mediumint | ||||
| smallint | ||||
| int | ||||
| int2 | ||||
| int4 | ||||
| int64 | ||||
| int8 | ||||
| integer | ||||
| serial8 | ||||
| tinyint | ||||
| INT | Hive | |||
| INT | Impala | |||
| BIGINT | MS SQL | |||
| MySQL | BIGINT | INTEGER | MySQL | |
| INT | ||||
| INTEGER | ||||
| MEDIUMINT | ||||
| SMALLINT | ||||
| TINYINT | ||||
| N/A | Oracle | |||
| INTEGER | Postgres | |||
| Redshift | BIGINT | INTEGER | Redshift | |
| INT | ||||
| INT2 | ||||
| INT4 | ||||
| INT8 | ||||
| INTEGER | ||||
| SMALLINT | ||||
| BIGINT | SiSense | |||
| Snowflake | BIGINT | INTEGER | Snowflake | |
| BYTEINT | ||||
| INT | ||||
| INTEGER | ||||
| SMALLINT | ||||
| TINYINT | ||||
| Synapse | BIGINT | INT | Synapse | |
| INT | ||||
| SMALLINT | ||||
| TINYINT | ||||
| INT | Thoughtspot | |||
| Source | Source Type | Base Type | Target Type | Target |
NUMERIC
The NUMERIC base type represents fixed-point fractional numbers
(real, numeric or decimal data types).
| Source | Source Type | Base Type | Target Type | Target |
|---|---|---|---|---|
| Generic | dec | NUMERIC | ||
| decimal | ||||
| fixed | ||||
| money | ||||
| number | ||||
| numeric | ||||
| smallmoney | ||||
| DECIMAL | Hive | |||
| DECIMAL | Impala | |||
| DECIMAL | MS SQL Server | |||
| MySQL | DEC | NUMERIC | MySQL | |
| DECIMAL | ||||
| FIXED | ||||
| NUMERIC | ||||
| NUMBER | Oracle | |||
| NUMERIC | PostgreSQL | |||
| Redshift | DECIMAL | NUMERIC | Redshift | |
| NUMERIC | ||||
| DECIMAL | SiSense | |||
| Snowflake | DECIMAL | NUMBER | Snowflake | |
| NUMBER | ||||
| NUMERIC | ||||
| Synapse | NUMERIC | NUMERIC | Synapse | |
| DECIMAL | ||||
| N/A | Thoughtspot | |||
| Source | Source Type | Base Type | Target Type | Target |
FLOAT
The FLOAT base type represents floating-point fractional numbers
(float or double data types).
| Source | Source Type | Base Type | Target Type | Target |
|---|---|---|---|---|
| Generic | binary_double | FLOAT | ||
| binary_float | ||||
| double | ||||
| double precision | ||||
| d_float | ||||
| float | ||||
| float4 | ||||
| float8 | ||||
| quad | ||||
| real | ||||
| FLOAT | Hive | |||
| FLOAT | Impala | |||
| FLOAT | MS SQL Server | |||
| MySQL | DOUBLE | FLOAT | MySQL | |
| DOUBLE PRECISION | ||||
| FLOAT | ||||
| REAL | ||||
| N/A | Oracle | |||
| REAL | PostgreSQL | |||
| Redshift | DOUBLE PRECISION | FLOAT | Redshift | |
| FLOAT | ||||
| FLOAT4 | ||||
| FLOAT8 | ||||
| REAL | ||||
| FLOAT | SiSense | |||
| Snowflake | FLOAT | DOUBLE | Snowflake | |
| DOUBLE PRECISION | ||||
| FLOAT | ||||
| FLOAT4 | ||||
| FLOAT8 | ||||
| REAL | ||||
| Synapse | FLOAT | FLOAT | Synapse | |
| REAL | ||||
| FLOAT | Thoughtspot | |||
| Source | Source Type | Base Type | Target Type | Target |
BOOLEAN
The BOOLEAN base type represents a true/false values.
| Source | Source Type | Base Type | Target Type | Target |
|---|---|---|---|---|
| Generic | bool | BOOLEAN | ||
| boolean | ||||
| BOOLEAN | Hive | |||
| BOOLEAN | Impala | |||
| BIT | MS SQL Server | |||
| N/A | MySQL | |||
| N/A | Oracle | |||
| BOOLEAN | PostgreSQL | |||
| Redshift | BOOL | BOOLEAN | Redshift | |
| BOOLEAN | ||||
| BIT | SiSense | |||
| Snowflake | BOOLEAN | BOOLEAN | Snowflake | |
| Synapse | BIT | BIT | Synapse | |
| BOOL | Thoughtspot | |||
| Source | Source Type | Base Type | Target Type | Target |
DATE
The DATE base type represents a date value without a time portion.
| Source | Source Type | Base Type | Target Type | Target | |
|---|---|---|---|---|---|
| Generic | date | DATE | DATE | ||
| N/A | Hive | ||||
| N/A | Impala | ||||
| DATE | MS SQL Server | ||||
| MySQL | DATE | DATE | MySQL | ||
| DATE | Oracle | ||||
| DATE | PostgreSQL | ||||
| Redshift | DATE | DATE | Redshift | ||
| DATE | SiSense | ||||
| Snowflake | DATE | DATE | Snowflake | ||
| Synapse | DATE | DATE | Synapse | ||
| DATE | Thoughtspot | ||||
| Source | Source Type | Base Type | Target Type | Target | |
TIMESTAMP
The TIMESTAMP base type represents a date value with a time portion.
| Source | Source Type | Base Type | Target Type | Target |
|---|---|---|---|---|
| Generic | datetime | TIMESTAMP | ||
| datetime2 | ||||
| datetimeoffset | ||||
| smalldatetime | ||||
| timestamp | ||||
| timestamptz | ||||
| timestamp_LTZ | ||||
| timestamp_NTZ | ||||
| TIMESTAMP_TZ | ||||
| timestamp with local time zone | ||||
| timestamp with time zone | ||||
| timestamp without time zone | ||||
| TIMESTAMP | Hive | |||
| TIMESTAMP | Impala | |||
| DATETIME2 | MS SQL Server | |||
| MySQL | DATETIME | TIMESTAMP | MySQL | |
| TIMESTAMP | ||||
| TIMESTAMP | Oracle | |||
| TIMESTAMP | PostgreSQL | |||
| Redshift | TIMESTAMP | TIMESTAMP | Redshift | |
| TIMESTAMPTZ | ||||
| TIMESTAMP WITH TIME ZONE | ||||
| TIMESTAMP WITHOUT TIME ZONE | ||||
| N/A | SiSense | |||
| Snowflake | DATETIME | TIMESTAMP | Snowflake | |
| TIMESTAMP | ||||
| TIMESTAMP_NTZ | ||||
| TIMESTAMP_LTZ | ||||
| TIMESTAMP_TZ | ||||
| Synapse | DATETIMEOFFSET | DATETIMEOFFSET | Synapse | |
| DATETIME | ||||
| DATETIME2 | ||||
| SMALLDATETIME | ||||
| TIME | ||||
| TIMESTAMP | Thoughtspot | |||
| Source | Source Type | Base Type | Target Type | Target |