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This section provides guides and references to use the MSSQL connector. Configure and schedule MSSQL metadata and profiler workflows from the Collate UI:

Requirements

The MSSQL user must grant SELECT privilege to fetch the metadata of tables and views.

View Definitions

Important: View lineage requires the VIEW DEFINITION (database-level) or VIEW ANY DEFINITION (server-level) permission. Without it, SQL Server returns each view’s definition as NULL and raises no error, so views are ingested without their SQL and no view lineage is created. Table metadata is not affected.

Usage and Lineage Considerations

To perform the query analysis for Usage and Lineage computation, the connector reads query history from SQL Server’s Query Store when it is enabled on a database. Query Store exposes this history through sys.query_store_query, sys.query_store_query_text, sys.query_store_plan, and sys.query_store_runtime_stats. Query Store keeps a durable, on-disk record of executed queries. The plan-cache Dynamic Management Views (DMVs) (sys.dm_exec_cached_plans, sys.dm_exec_query_stats, and sys.dm_exec_sql_text) are evicted on server restart, memory pressure, or plan recompilation, and can silently return incomplete history. Query Store is auto-detected per database. No configuration is needed. When ingestAllDatabases is enabled, each database is read from its own best source independently: databases with Query Store use it, and the rest fall back to the plan-cache DMVs, so one database without Query Store never downgrades the others.
Tip: Enable Query Store on the databases you ingest, for reliable and durable Usage and Lineage history.
To check whether Query Store is enabled on a database, and how it is currently operating:
To enable it:
The default QUERY_CAPTURE_MODE on SQL Server 2019 and later is AUTO, which can skip queries that only run a few times, such as a one-off data migration statement. Setting it to ALL ensures every query is captured for lineage. Set STALE_QUERY_THRESHOLD_DAYS to cover at least your ingestion lookback window, so queries are not purged before they are read. Query Store’s default SIZE_BASED_CLEANUP_MODE purges the oldest queries to stay within MAX_STORAGE_SIZE_MB, which reduces the risk of Query Store switching to read-only. Under heavy write load, cleanup can still fall behind, and Query Store can switch to read-only temporarily until it catches up.
Important: Query Store needs two permissions together. The following database-level grant lets sys.database_query_store_options and Query Store’s other metadata views succeed, but the query text comes from sys.query_store_query_text, which needs the server-level grant. Without the server-level grant, usage and lineage queries can run without error while returning no query text.
Database-level, for Query Store metadata: VIEW DATABASE STATE (SQL Server 2016–2019) or VIEW DATABASE PERFORMANCE STATE (SQL Server 2022 and later).
Server-level, for the query text and the plan-cache DMV fallback: VIEW SERVER STATE (SQL Server 2019 and earlier) or VIEW SERVER PERFORMANCE STATE (SQL Server 2022 and later).
Exact grant names and tiers can differ on Azure SQL Database and Azure SQL Managed Instance. Check sys.database_query_store_options and the Microsoft documentation for your instance.

For Remote Connection

1. Confirm SQL Server Is Running

Confirm that the SQL Server instance you want to connect to is running.

2. Allow Remote Connection on SSMS (Microsoft SQL Server Management Studio)

This step allows SQL Server to accept remote connection requests. Remote Connection

3. Configure Windows Firewall

If using SQL Server on Windows, configure the firewall on the computer running SQL Server to allow access.
  1. On the Start menu, select Run, type WF.msc, and then select OK.
  2. In the Windows Firewall with Advanced Security, in the left pane, right-click Inbound Rules, and then select New Rule in the action pane.
  3. In the Rule Type dialog box, select Port, and then select Next.
  4. In the Protocol and Ports dialog box, select TCP. Select Specific local ports, and then type the port number of the instance of the Database Engine, such as 1433 for the default instance. Select Next.
  5. In the Action dialog box, select Allow the connection, and then select Next.
  6. In the Profile dialog box, select any profiles that describe the computer connection environment when you want to connect to the Database Engine, and then select Next.
  7. In the Name dialog box, type a name and description for this rule, and then select Finish. For more information, see the Microsoft documentation on configuring a Windows Firewall for Database Engine access.

Metadata Ingestion

To ingest metadata from MSSQL, you need to create a service connection. The service connects MSSQL with Collate. Once you create a service, Collate automatically starts ingesting metadata.

Step 1: Add New Service

  1. In the left navigation, click Connections.
  2. On the Connections page, click Add New Service.
Add New Service

Step 2: Select a Service and Connector

From the service type dropdown, select Database Services, then click the MSSQL connector tile. Select Service

Step 3: Add Service Name and Description

  • Enter a unique, descriptive Service Name. Collate identifies services by their service name. Enter a name that distinguishes this deployment from other MSSQL services you are ingesting metadata from.
  • Optional: Enter a Description for the service.
Add New Service Name
Note: The service name cannot be changed after it is set.

Step 4: Configure Connection Options

Specify where ingestion runs, provide your source credentials, and verify the connection.

Select Ingestion Runner

Select an Ingestion Runner: the runner where the ingestion pipeline will execute. Add Name and Select Ingestion Runner

Enter Connection Details

Enter the connection details for MSSQL. The right-hand panel in the UI displays inline help for each field. Configure Service Connection
  • Connection Scheme: Defines how to connect to MSSQL. Collate supports mssql+pytds, mssql+pyodbc, and mssql+pymssql. If using Windows Authentication from a Linux deployment, use pymssql.
  • Username: Specify the User to connect to MSSQL. It should have enough privileges to read all the metadata.
  • Password: Password to connect to MSSQL.
  • Host and Port: Enter the fully qualified hostname and port number for your MSSQL deployment in the Host and Port field.
  • URI String: In case of a pyodbc connection.
  • Database: The initial database to establish a connection to the data source.
  • Ingest All Databases: Enable this option to ingest multiple databases in addition to the database specified in the Database field.

Advanced Configuration

Database Services include an Advanced Configuration section for passing extra arguments to the connector and, if needed, changing the connection scheme. This section is only required for advanced connectivity scenarios or customizations.
  • Connection Options (Optional): Enter the details for any additional connection options that can be sent to database during the connection. These details must be added as Key-Value pairs.
  • Connection Arguments (Optional): Enter the details for any additional connection arguments such as security or protocol configs that can be sent during the connection. These details must be added as Key-Value pairs.
Tip: When using a Hybrid Ingestion Runner, any sensitive credential fields—such as passwords, API keys, or private keys—must reference secrets using the following format:
This applies only to fields marked as secrets in the connection form (these typically mask input and show a visibility toggle icon). For more information about managing secrets in hybrid setups, see the Hybrid Ingestion Runner Secret Management Guide.

Test Connection

After entering the credentials, click on Test Connection and Save the changes. Test Connection

Step 5: Configure Ingestion Options

In the What to Ingest step, use filter patterns to control which assets Collate ingests from your database service. Filter patterns use regular expressions applied to asset names.

How Filter Patterns Work

  • Include: Add one or more comma-separated regular expressions. Collate ingests only assets whose names match at least one expression. Leave blank to include all assets.
  • Exclude: Add one or more comma-separated regular expressions. Collate skips any asset whose name matches an expression. Leave blank to exclude nothing.
Rules match asset names using one of five expressions:
  • contains: matches any name containing the value. For example, sales matches my_sales_data and sales_2024.
  • starts with: matches names beginning with the value. For example, prod_ matches prod_db and prod_schema.
  • ends with: matches names ending with the value. For example, _raw matches events_raw and logs_raw.
  • is exactly: matches the exact name only. For example, analytics matches only analytics.
  • matches regex: matches names using a regular expression. For example, ^prod_.*_v\d+$ matches prod_events_v1.
When both Include and Exclude are set, Exclude takes priority.
Tip: Leave all filter patterns empty to ingest all databases, schemas, and tables available in the source.

Filter Options

The Database, Schema, Table, and Stored Procedure sections each include the following filter options:
  • Database: Controls which databases Collate ingests from the source.
  • Schema: Controls which schemas within the ingested databases are included.
  • Table: Controls which tables and views within the ingested schemas are included.
  • Stored Procedure: Controls which stored procedures are included in metadata ingestion.
Each section provides the following controls:
  • Scan Mode: Choose one of the following scan modes:
    • Scan all: Ingests every asset of that type the connector can access. This is the default.
    • Only specific: Enables include rules so only assets matching at least one rule are ingested.
  • Exclude system toggle: Use this toggle to automatically filter out system-reserved names defined by the connector—for example, Exclude system databases for the Databases section.
  • Always exclude: Add permanent exclusion rules (shown in red). Assets matching these rules are never ingested, regardless of include rules.
  • Preview: Shows a real-time summary of what will be in scope based on your current rules.
  • Include rules (available only in Only specific mode): Click + Add to define a rule. Added rules appear as chips. An asset is included if it matches any rule.
Tip: If AutoPilot is enabled, usage tracking, data lineage, and other downstream workflows start automatically after the first metadata ingestion completes.

Step 6: Create & Deploy

Click Create & Deploy to deploy the agent and start the first metadata ingestion run. Collate saves the service configuration and immediately begins pulling metadata from the source. To monitor ingestion progress or view the service you just added, go to Connections in the left navigation and select your service.

Configure Metadata Agent and Schedule Ingestion

The Metadata Agent extracts schemas, tables, columns, and other structural metadata from your source and keeps your Collate catalog in sync. It powers discovery, lineage, and governance across your data assets. When you click Create & Deploy, Collate automatically deploys a Metadata Agent for this service and triggers the first ingestion run. View its status and run history from the Agents tab on the service detail page. To configure the additional Metadata Agent and schedule ingestion, follow these steps:
  1. In the left navigation, click Connections and select your service.
  2. Click the Agents tab.
  3. Click Add Agent and select Metadata from the dropdown. Add Metadata Agent For some services, the dropdown is not available and clicking Add Agent takes you directly to the agent configuration page.
  4. On the Configure Ingestion page, do the following and click Next.
    • Name this Ingestion: Enter a unique recognizable name for this ingestion pipeline. Name this Ingestion
    • Agent Setup: Configure core parameters for metadata extraction. The following fields are available: Agent Setup
    • Filter Patterns: Apply include or exclude rules to scope which databases, schemas, tables, and stored procedures this agent ingests. For more information about various filter options, see Step 5: Configure Ingestion Options. Filter Patterns
    • Scope & Behaviour: Control how the agent handles metadata during ingestion. Toggle each option on or off based on your needs:
      Note: Available toggles vary by connector. Stored procedure options only appear for connectors that support stored procedures.
      Scope & Behaviour
    • Advanced Config: Optional connector-specific settings such as Include Views and Extract JSON Schema. Advanced Config
  5. On the Schedule Interval page, set when the agent runs:
    • Schedule: Choose a preset interval (Hourly, Daily, Weekly, Monthly) or enter a custom cron expression.
    • On-Demand: No automatic schedule; trigger the agent manually when needed.
    Schedule Interval
  6. Click Add to deploy the agent.

Reverse Metadata

  • Description Management: MSSQL supports description updates at the following levels:
    • Schema level
    • Table level
    • Column level
  • Owner Management: MSSQL supports owner management at the following levels:
    • Database level
    • Schema level
  • Tag Management: Tag management is not supported for MSSQL.
  • Custom SQL Template: MSSQL supports custom SQL templates for metadata changes. The template is interpreted using python f-strings. Here are examples of custom SQL queries for metadata changes:
    The list of variables for custom SQL can be found here.
For more information about reverse metadata ingestion, see Reverse Metadata Application.

Troubleshooting

MSSQL Troubleshooting

Learn more about how to troubleshoot common MSSQL connector issues and resolve configuration or ingestion errors.