SQL Server to Databricks
real-time replication
TwinCommit replicates Microsoft SQL Server to Databricks in real time by reading the SQL Server transaction log and applying every committed change exactly once and in commit order. Use it to feed Databricks with live SQL Server data for analytics, AI and reporting, with no triggers or capture tables on the source.
SQL Server
log reader
commit-ordered · exactly-once
Databricks
native writer
How capture works on SQL Server
TwinCommit reads the active and backed-up transaction log directly, so you do not need SQL Server Agent CDC jobs or change tables.
Prerequisites
- ✓FULL recovery model
- ✓Primary key on each replicated table
- ✓VIEW SERVER STATE and db_owner on the source database
How apply works on Databricks
Micro-batches are staged as Parquet in your cloud storage and applied with Delta MERGE through a SQL warehouse. Deletes, updates and ordering are preserved per key.
Requirements
- ✓A SQL warehouse or all-purpose cluster
- ✓A Unity Catalog volume or external location for staging
- ✓A service principal with MODIFY on the target schema
Setup
Set up SQL Server → Databricks in four steps
- 1
Prepare SQL Server
Run twincommit check. It verifies full recovery model and the other prerequisites, and prints the exact fix for anything missing.
- 2
Point at Databricks
Add a target block for Databricks. TwinCommit can generate target DDL with twincommit ddl -apply.
- 3
Snapshot
twincommit snapshot copies each table under a brief share lock and records the exact log position.
- 4
Stream
twincommit run streams every committed change from that position, exactly once and in commit order.
source:
type: sqlserver
dsn: ${SOURCE_DSN}
target:
type: databricks
host: adb-1234567890.12.azuredatabricks.net
warehouse: replication-wh
catalog: main
schema: replica
tables:
- source: SALES.ORDERS
- source: SALES.ORDER_LINES
exclude_columns: [INTERNAL_NOTES]SQL Server to Databricks replication FAQ
How does TwinCommit replicate SQL Server to Databricks?
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TwinCommit reads changes from the SQL Server transaction log, buffers them per transaction, and applies each committed transaction to Databricks in commit order. Micro-batches are staged as Parquet in your cloud storage and applied with Delta MERGE through a SQL warehouse. Deletes, updates and ordering are preserved per key.
Does SQL Server to Databricks replication need triggers or capture tables?
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No. TwinCommit reads the SQL Server log directly and creates no objects in the source database.
Is SQL Server to Databricks replication exactly-once?
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Yes. TwinCommit commits its checkpoint in the same Databricks transaction as the data, so a crash or restart never loses or duplicates a transaction.
What SQL Server versions are supported?
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SQL Server 2016–2025 · Azure SQL Managed Instance · Azure SQL Database (target).
Stream SQL Server to Databricks today.
Download the free Developer edition, or have one of our replication engineers walk you through a migration plan.