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Database connectors let Summand query a live warehouse and refresh analysis on demand. Available on Enterprise plans.

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Supported engines

PostgreSQL

Versions 11+. Read-only credentials recommended.

MySQL

Versions 5.7+ and MySQL 8. Compatible with MariaDB.

Snowflake

Username + password authentication.

Azure SQL

Azure SQL Database and Managed Instance.
For Databricks (with UniForm), see Delta Sharing. For Databricks without UniForm, Redshift, BigQuery, Oracle, and SaaS sources, see Fivetran.

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What Summand needs

A user with read-only access to the schemas and tables you intend to analyze. Specifically:
  • SELECT on the target tables
  • USAGE on the schemas (Postgres / Snowflake)
  • INFORMATION_SCHEMA access for schema discovery
Summand never executes writes, never reads system catalogs beyond INFORMATION_SCHEMA, and never executes user-supplied SQL.

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Network access

Summand connects from two fixed egress IP addresses, listed in Settings → Connectivity. Share them with your network team to allowlist. Summand reaches your database over its public endpoint. PrivateLink, VPC peering and SSH tunnels are not supported, so a database with no public endpoint can’t be connected directly. For those, contact our sales team.

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Setup

1

Create a read-only user in your database

Use the SQL appropriate for your engine. For Postgres:
2

Add the connector in Summand

From the Connectors page, click Add connector → PostgreSQL (or MySQL / Snowflake). Provide host, port, database, and the read-only credentials. Summand validates connectivity before saving.
3

Pick tables

Summand discovers all tables you have SELECT on. Choose which ones to enable as datasets. You can enable more later from the connector page.Each enabled table becomes a dataset. Baseline column-stats run automatically. From there, chat, create views, or set up experiments — there’s no per-dataset configuration step.

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Refresh

Click Refresh on a dataset to re-read the source table into Summand’s copy. Each run writes a new snapshot of the dataset’s Iceberg table. Earlier snapshots stay queryable for at least 30 days by default. You can also put a dataset on a schedule: hourly, every 3, 6 or 12 hours, daily, or weekly. Each dataset has a sync mode:
  • Full refresh (default) re-reads the whole table.
  • Incremental append reads only rows whose cursor column is past the last run’s value.
  • Incremental merge does the same, and updates existing rows by primary key.
Refresh updates the data. Analysis components run when you ask for them in chat or through an experiment.

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Credential handling

  • Database passwords are encrypted with AWS KMS and stored in AWS Secrets Manager.
  • Plaintext credentials are never logged.
  • Connection strings are never exposed in the UI or API responses.
  • You can rotate credentials at any time from Settings → Connectors → Edit.

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Removing a connector

Deleting a connector starts a background job that deletes each of its datasets and their stored data, then the connector’s stored credentials. Views and experiments built on those datasets stay in place. If you re-add the connector, its tables come back as new datasets without their earlier analysis history.