Microsoft SQL Server

For context on getting started with ingestion, check out our metadata ingestion guide.

Setup

To install this plugin, run pip install 'acryl-datahub[mssql]'.

We have two options for the underlying library used to connect to SQL Server: (1) python-tds and (2) pyodbc. The TDS library is pure Python and hence easier to install, but only PyODBC supports encrypted connections.

Capabilities

This plugin extracts the following:

Metadata for databases, schemas, views and tables
Column types associated with each table/view
Table, row, and column statistics via optional SQL profiling

Quickstart recipe

Check out the following recipe to get started with ingestion! See below for full configuration options.

For general pointers on writing and running a recipe, see our main recipe guide.

source:
  type: mssql
  config:
    # Coordinates
    host_port: localhost:1433
    database: DemoDatabase

    # Credentials
    username: user
    password: pass

sink:
  # sink configs

Example: using ingestion with ODBC and encryption

This requires you to have already installed the Microsoft ODBC Driver for SQL Server. See https://docs.microsoft.com/en-us/sql/connect/python/pyodbc/step-1-configure-development-environment-for-pyodbc-python-development?view=sql-server-ver15

source:
  type: mssql
  config:
    # Coordinates
    host_port: localhost:1433
    database: DemoDatabase

    # Credentials
    username: admin
    password: password

    # Options
    uri_args:
      driver: "ODBC Driver 17 for SQL Server"
      Encrypt: "yes"
      TrustServerCertificate: "Yes"
      ssl: "True"

sink:
  # sink configs

Config details

Note that a . is used to denote nested fields in the YAML recipe.

As a SQL-based service, the Athena integration is also supported by our SQL profiler. See here for more details on configuration.

Field	Default	Description
`username`		MSSQL username.
`password`		MSSQL password.
`host_port`	`"localhost:1433"`	MSSQL host URL.
`database`		MSSQL database.
`database_alias`		Alias to apply to database when ingesting.
`use_odbc`	`False`	See https://docs.sqlalchemy.org/en/14/dialects/mssql.html#module-sqlalchemy.dialects.mssql.pyodbc.
`uri_args.<uri_arg>`		Arguments to URL-encode when connecting. See https://docs.microsoft.com/en-us/sql/connect/odbc/dsn-connection-string-attribute?view=sql-server-ver15.
`env`	`"PROD"`	Environment to use in namespace when constructing URNs.
`options.<option>`		Any options specified here will be passed to SQLAlchemy's `create_engine` as kwargs. See https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine for details.
`table_pattern.allow`		List of regex patterns for tables to include in ingestion.
`table_pattern.deny`		List of regex patterns for tables to exclude from ingestion.
`table_pattern.ignoreCase`	`True`	Whether to ignore case sensitivity during pattern matching.
`schema_pattern.allow`		List of regex patterns for schemas to include in ingestion.
`schema_pattern.deny`		List of regex patterns for schemas to exclude from ingestion.
`schema_pattern.ignoreCase`	`True`	Whether to ignore case sensitivity during pattern matching.
`view_pattern.allow`		List of regex patterns for views to include in ingestion.
`view_pattern.deny`		List of regex patterns for views to exclude from ingestion.
`view_pattern.ignoreCase`	`True`	Whether to ignore case sensitivity during pattern matching.
`include_tables`	`True`	Whether tables should be ingested.
`include_views`	`True`	Whether views should be ingested.

Compatibility

Coming soon!

Questions

If you've got any questions on configuring this source, feel free to ping us on our Slack!

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