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Stacksync syncs with PostgreSQL, MySQL, MongoDB, Microsoft SQL Server, Oracle Database, DynamoDB, CockroachDB, Amazon Aurora, MariaDB, and managed Postgres flavors like Neon, Supabase, RDS, and Cloud SQL. Each connector handles full reads, CDC-based streaming changes, and bidirectional writes. New databases are added on request, most go from request to production support within 3 weeks.

Stacksync prefers native change-data-capture wherever the database supports it: Postgres logical replication, MySQL binlog, MongoDB change streams, DynamoDB Streams, SQL Server CDC. CDC means sub-second latency and no production load. Where CDC is not available, Stacksync falls back to indexed polling on a configurable interval (every 30 seconds to 5 minutes). Triggers are not used by default, they can degrade source write performance, but they are available as an opt-in for legacy databases.

Yes, Postgres-to-Salesforce is one of the most common Stacksync patterns. Stacksync uses Postgres logical replication to stream every INSERT, UPDATE, and DELETE to Salesforce within seconds. The reverse direction works too: changes in Salesforce flow back into Postgres via the Salesforce CDC stream. Field-level mapping, conflict resolution, and selective sync (only sync rows matching a predicate) are all configurable in the dashboard.

Schema drift is detected on every sync run. Additive changes (new columns, new tables) are auto-included once you approve them in the mapping UI. Type-compatible changes (varchar widened, int to bigint) are applied automatically. Breaking changes (column dropped, type changed in an incompatible way) pause the affected sync and surface in the dashboard for review. Optionally, schema-drift events can fire webhooks so your data team gets notified in Slack the moment a source schema changes.

For CDC-based sources (Postgres logical replication, MySQL binlog, MongoDB change streams) the typical end-to-end latency is 200 milliseconds to 2 seconds, from commit on the source database to applied write at the destination. Polling-based sources see 30 seconds to 5 minutes depending on poll interval. Streaming destinations (Postgres, Snowflake) match source latency; rate-limited app destinations (Salesforce, HubSpot) add 300 to 800 milliseconds of API call time.

Yes, Stacksync can read from a read replica or a logical replication subscriber to keep load off the primary. For Postgres, Stacksync connects to either the primary (for logical replication) or a hot standby (for polling-based sync). For MySQL, Stacksync reads binlog from any replica that has it enabled. Bidirectional sync that writes back to the source always targets the primary, but read-only sync paths can be isolated to replicas.

All Stacksync database connections require TLS 1.2 or higher. Credentials are stored in a hardware-backed key vault, encrypted at rest with AES-256, and rotated automatically. Data in flight through the Stacksync control plane is encrypted end-to-end; data at rest in queue durability storage is encrypted with per-tenant keys. Customer-managed encryption keys (CMEK) are available for enterprise plans, credentials and data both encrypted under keys your team controls in AWS KMS or GCP KMS.