DBSync Developer Platform
Build, automate, and extend data synchronization workflows using DBSync’s programmable interfaces, replication engine, and connector framework.
DBSync is designed to run as infrastructure: scriptable, observable, and safe to operate in production environments.
Core integration and automation layers
DBSync exposes multiple control surfaces that allow developers to run, automate, and integrate synchronization workflows into existing systems.
1. CLI mode
Run and manage DBSync directly from the command line.
The CLI enables developers to operate sync workflows without relying on a web UI, making it suitable for headless environments and automated deployments.
The CLI is commonly used in infrastructure-as-code setups where repeatability and automation are required.
Supported operations
- Initialize and configure sync projects
- Define source and target connections
- Execute sync jobs on demand
- Monitor execution status and logs
- Integrate sync jobs into cron jobs or CI/CD pipelines
2. Upgrade utility
Safely upgrade agents, schemas, and sync engines without breaking existing pipelines.
The upgrade utility manages version compatibility and migrations across DBSync components.
This allows teams to apply updates without manually reconfiguring or redeploying pipelines.
Capabilities
- Detects version mismatches between agents and engines
- Applies schema and metadata migrations when required
- Supports rolling upgrades with minimal disruption
- Provides rollback safety in case of failed upgrades
3. Web API
Control and observe DBSync programmatically through REST APIs.
The Web API enables external systems to interact with DBSync as part of broader platforms or internal tooling.
Common use cases
- Trigger sync jobs from external applications
- Query job status, logs, and execution history
- Manage environments, profiles, and configurations
- Integrate synchronization into internal dashboards or services
Security
- API key–based authentication
- OAuth support for managed environments
4. Webhooks
Receive real-time notifications about synchronization events.
Webhooks allow DBSync to emit events that external systems can react to, enabling event-driven data workflows.
Webhooks are commonly used to trigger downstream processing, alerting, or workflow orchestration.
Supported events
- Sync job started
- Sync job completed
- Sync job failed
- Data change detected
- Validation or reconciliation alerts
Data synchronization engine
This layer defines how DBSync detects, moves, and validates data between systems.
Change Data Capture (CDC)
Track inserts, updates, and deletes at the source and replicate only the changes.
DBSync’s CDC engine continuously monitors source systems and streams incremental changes to targets.
Key characteristics
- Change-based replication instead of full reloads
- Reduced load on source systems
- Near-real-time or scheduled synchronization modes
- Maintains replication state to prevent duplicates or data loss
CDC is used for both operational replication and analytics pipelines where freshness and efficiency matter.
Data compare
Validate and reconcile data between source and target systems.
The Data Compare engine allows developers to verify synchronization accuracy and detect drift over time.
Supported workflows
- Post-migration validation
- Ongoing consistency checks
- Detection of missing or mismatched records
- Generation of reconciliation reports
This is commonly used in regulated, financial, or high-integrity data environments.
Connector development framework
Extend DBSync to support new databases, APIs, and SaaS platforms.
The connector framework allows developers and partners to build custom connectors that integrate seamlessly with the core sync engine.
Connector profile creation
Define how DBSync interacts with a new system.
Connector profiles specify:
- Authentication mechanisms
- Schema discovery logic
- Field mappings and transformations
- Sync rules and filters
- Change detection behavior
Custom connectors created using this framework behave like native connectors within DBSync.
Supported connector use cases
Connectors built on DBSync support a range of synchronization patterns, including:
- Database-to-database replication
- SaaS-to-database ingestion
- API-to-API synchronization
- One-way and two-way data syncs
- Event-driven pipelines using CDC
- Data validation using Data Compare
- Workflow orchestration using Webhooks
These patterns can be combined to build internal automation or commercial data integrations.
How DBSync replication works in production
1. Detects changes at the source
Captures new and updated records without relying on full reloads.
2. Tracks state incrementally
Maintains sync state so pipelines resume predictably.
3. Loads warehouse-ready data
Adapts to evolving source schemas without breaking downstream jobs.
4. Loads warehouse-ready data
Data stands structured and analytics-friendly.
How DBSync replication works in production
What DBSync handles so you don’t have to
- Incremental logic and offsets
- Schema drift edge cases
- Retry and failure handling
- Source-specific quirks
Operating DBSync in production
DBSync is designed to run continuously with minimal manual intervention.
This enables teams to deploy and maintain long-running data pipelines with predictable behavior.
Across all integration layers, the platform supports:
- Scriptable execution
- Incremental state management
- Observable job status and logs
- Safe upgrades and rollback mechanisms
Get Started
This is where most custom replication pipelines quietly turn into long-term tech debt.