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

Capability	Status	Details
Platform Instance	✔️	link

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
    use_odbc: "True"
    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.
`platform_instance`	None	The Platform instance to use while 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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