Driver for Teradata¶

Driver for Teradata v0.1.1

Driver Version v0.1.1 Tested With Teradata 20

This driver provides access to Teradata .

Note

This project is not affiliated with Teradata.

Installation & Quickstart¶

Important

This driver is available from Columnar’s private driver registry. Before installing it, create an account at cloud.columnar.tech and click to activate a 14-day free trial. Then authenticate to the registry:

dbc auth login

The driver can be installed with dbc :

dbc install teradata

To use the driver:

Install the Teradata Tools and Utilities .
Set LD_LIBRARY_PATH, DYLD_LIBRARY_PATH, PATH, or otherwise make sure the Teradata client libraries are discoverable by your application, if needed.
Provide the connection string as the uri parameter.

Connecting¶

To use the driver, provide a URI as the uri option. The driver supports URI format and Teradata’s own connection strings, but URIs are recommended.

from adbc_driver_manager import dbapi

dbapi.connect(
  driver="teradata",
  db_kwargs={
      "uri": "teradata://dbc:dbc@127.0.0.1:1025"
  }
)

Note: The example above is for Python using the adbc-driver-manager package but the process will be similar for other driver managers. See adbc-quickstarts .

Connection String Format¶

teradata://user:password@host[:port]

Components:

scheme: teradata:// (required)
user/password: For standard database authentication.
host: (required) The hostname or IP address of the Teradata database server.
port: (optional) Defaults to 1025.

Note

Reserved characters in URI elements must be URI-encoded. For example, @ becomes %40.

Examples:

teradata://dbc:dbc@127.0.0.1
teradata://dbc:dbc@dbhost.local:1025

Feature & Type Support¶

Feature	Support
Bulk Ingestion	Create	✅
	Append	✅
	Create/Append	✅
	Replace	✅
	Temporary Table	❌
	Specify target catalog	✅
	Specify target schema	❌
	Non-nullable fields are marked NOT NULL	❌
Catalog (GetObjects)	depth=catalogs	✅
	depth=db_schemas	✅
	depth=tables	✅
	depth=columns (all)	✅
Get Parameter Schema	❌
Get Table Schema	❌
Prepared Statements	✅
Transactions	❌

Types¶

Teradata to Arrow¶

Teradata Type	Arrow Type
BIGINT	int64
BLOB	large_binary
BYTEINT	int8
CHARACTER(n) CHARACTER SET UNICODE	string ⚠️ [1]
CLOB CHARACTER SET LATIN	large_string
CLOB CHARACTER SET UNICODE	large_string
DATE	date32[day]
DOUBLE PRECISION	double
INT	int32
INTERVAL DAY(n)	month_day_nano_interval
INTERVAL DAY(n) TO HOUR	month_day_nano_interval
INTERVAL DAY(n) TO MINUTE	month_day_nano_interval
INTERVAL DAY(n) TO SECOND(n)	month_day_nano_interval
INTERVAL HOUR(n)	month_day_nano_interval
INTERVAL HOUR(n) TO MINUTE	month_day_nano_interval
INTERVAL HOUR(n) TO SECOND(n)	month_day_nano_interval
INTERVAL MINUTE(n)	❌ [2]
INTERVAL MINUTE(n) TO SECOND(n)	month_day_nano_interval
INTERVAL MONTH(n)	❌ [2]
INTERVAL SECOND(n, n)	month_day_nano_interval
INTERVAL YEAR(n)	month_day_nano_interval
INTERVAL YEAR(n) TO MONTH	month_day_nano_interval
NUMBER	decimal256
NUMERIC	decimal128
SMALLINT	int16
TIME(0)	time32[s]
TIME(1)	time32[ms]
TIME(2)	time32[ms]
TIME(3)	time32[ms]
TIME(4)	time64[us]
TIME(5)	time64[us]
TIME(6)	time64[us]
TIMESTAMP	timestamp[s]
TIMESTAMP WITH TIME ZONE	timestamp[s] (with time zone)
TIMESTAMP(0)	timestamp[s]
TIMESTAMP(0) WITH TIME ZONE	timestamp[s] (with time zone)
TIMESTAMP(1)	timestamp[ms]
TIMESTAMP(1) WITH TIME ZONE	timestamp[ms] (with time zone)
TIMESTAMP(2)	timestamp[ms]
TIMESTAMP(2) WITH TIME ZONE	timestamp[ms] (with time zone)
TIMESTAMP(3)	timestamp[ms]
TIMESTAMP(3) WITH TIME ZONE	timestamp[ms] (with time zone)
TIMESTAMP(4)	timestamp[us]
TIMESTAMP(4) WITH TIME ZONE	timestamp[us] (with time zone)
TIMESTAMP(5)	timestamp[us]
TIMESTAMP(5) WITH TIME ZONE	timestamp[us] (with time zone)
TIMESTAMP(6)	timestamp[us]
TIMESTAMP(6) WITH TIME ZONE	timestamp[us] (with time zone)
VARBYTE	binary
VARCHAR(n) CHARACTER SET LATIN	string
VARCHAR(n) CHARACTER SET UNICODE	string

Arrow to Teradata¶

Arrrow Type	Teradata Type
Arrrow Type	Bind	Ingest
binary	VARBYTE [3]	VARBINARY
binary_view	VARBYTE [3]	VARBINARY
bool	BYTEINT [4]	BOOLEAN
date32[day]	DATE
decimal128	NUMERIC
double	DOUBLE PRECISION
fixed_size_binary	VARBYTE	VARBINARY
float	REAL
halffloat	REAL	(not tested)
int16	SMALLINT
int32	INT
int64	BIGINT
large_binary	VARBYTE [3]	VARBINARY
large_string	VARCHAR
string	VARCHAR
string_view	VARCHAR
time32[ms]	TIME
time32[s]	TIME
time64[ns]	TIME
time64[us]	TIME
timestamp[ms]	TIMESTAMP(3)
timestamp[ms] (with time zone)	TIMESTAMP(3) WITH TIME ZONE
timestamp[ns]	TIMESTAMP(9) [5]	TIMESTAMP(9)
timestamp[ns] (with time zone)	TIMESTAMP(9) WITH TIME ZONE [5]	TIMESTAMP(9) WITH TIME ZONE
timestamp[s]	TIMESTAMP(0)
timestamp[s] (with time zone)	TIMESTAMP(0) WITH TIME ZONE
timestamp[us]	TIMESTAMP(6)
timestamp[us] (with time zone)	TIMESTAMP(6) WITH TIME ZONE