SQL Server integration for Dimension Labs
If your conversations already land in a SQL Server or Azure SQL Database table, you can send them to Dimension Labs from there. A scheduled job on your side queries the rows that are new since its last run and posts each message to the universal API.
- Platform
- Microsoft SQL Server
- Type
- Databases and storage
- Connects by
- Universal API
- Setup
- 5 steps
- Guide checked
- 2026-10-26, against Microsoft's and node-mssql's documentation
Every SQL Server message, in the same shape as everything else.
Each record lands in the Dimension Labs conversation format, so Dimensions, reports and the agent work the same way as for every other source.
body text Skip rows where it is empty. Strip HTML if bodies are HTML.
customer_id userId If it is null, use the sessionId.
sender_type incoming true only when the customer wrote it. Agent and bot rows are false.
conversation_id sessionId Replace any colons.
conversation_id conversationId Same value as sessionId.
sent_at dimensionlabs_timestamp Pass the Date through toMillis.
message_id, channel platformJson Add any join keys you have, such as an account or store id.
5 steps. Then it runs on its own.
A small job on your side reads SQL Server through its API and posts each message to the Dimension Labs universal API. The guide gives the steps, the field mapping and the code. Run the job once for history, then every 15 minutes. A live source is enriched automatically every day; history is enriched with a backfill.
Open the full SQL Server guide ›- 01Get access
- 02Query new rows
- 03Map the columns
- 04Send it
- 05Run it
What you need
- A SQL Server login that can create logins or users, and grant access to the table that holds your conversations.
- The server name and database, and network access to it from wherever the job runs. Azure SQL Database blocks all access to its public endpoint until you add a firewall rule for the job's IP address (Azure SQL Database IP firewall rules).
- A Dimension Labs API key for a new Universal API source.
[03] What you can ask
Questions teams answer with SQL Server data.
- What do customers say before a refund?
- Which accounts are describing the same problem?
- What changed after the release?
SQL Server integration questions
Does Dimension Labs integrate with SQL Server?
Yes. A small job on your side reads SQL Server through its API and posts each message to the Dimension Labs universal API. The guide gives the steps, the field mapping and the code. The setup guide was checked against Microsoft's and node-mssql's documentation on 2026-10-26.
What SQL Server data does Dimension Labs bring in?
If your conversations already land in a SQL Server or Azure SQL Database table, you can send them to Dimension Labs from there. A scheduled job on your side queries the rows that are new since its last run and posts each message to the universal API.
What do I need to connect SQL Server?
A SQL Server login that can create logins or users, and grant access to the table that holds your conversations. The server name and database, and network access to it from wherever the job runs. Azure SQL Database blocks all access to its public endpoint until you add a firewall rule for the job's IP address (Azure SQL Database IP firewall rules). A Dimension Labs API key for a new Universal API source.
How often does SQL Server data update?
Run the job once for history, then every 15 minutes. A live source is enriched automatically every day; history is enriched with a backfill.
Can I connect a platform that is not SQL Server?
Yes. Any platform with an API connects through the same universal API, and any tool with an export button works as a file upload. The integrations page lists the platforms with a written guide.
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