01 / Latency
Data arrives too late
Periodic jobs leave applications and analytics working from an increasingly stale view of operational data.
Solution · Real-time integration
CDC streaming without source overhead
Capture committed database changes from transaction logs and deliver them continuously to databases, event streams, and data platforms—without polling full tables.
- 01 Read the native change stream
- 02 Buffer and route through Core Hub
- 03 Apply changes in order
The challenge
Batch windows hide what changed
Polling and scheduled extracts create stale copies, consume source resources, and make recovery harder when networks or targets pause.
02 / Source load
Polling competes with production
Repeated table scans consume CPU, I/O, and connections on the systems carrying the business workload.
03 / Reliability
Interruptions create gaps
Fragile scripts make it difficult to preserve ordering and resume safely after maintenance or network loss.
How it works
From commit log to target, continuously
Gluesync places lightweight agents close to each system, captures committed changes, and coordinates delivery through Core Hub.
- 01
Capture
Read the native change stream
Source agents read transaction logs, journals, or native CDC APIs instead of repeatedly scanning tables.
- 02
Coordinate
Buffer and route through Core Hub
Durable local queues and pipeline state preserve events while a target or network path is unavailable.
- 03
Deliver
Apply changes in order
Target agents translate inserts, updates, and deletes for the destination and resume from acknowledged progress.
Gluesync capabilities
A CDC foundation built for heterogeneous estates
Use the same control plane for initial loading, continuous capture, transformation, and operational recovery.
01
Log-based capture
Capture committed row changes with low source impact across supported relational and NoSQL engines.
- Transaction-log and journal readers
- Insert, update, and delete handling
- Configurable low-latency polling
02
Initial load to CDC handoff
Seed the target with a snapshot, then continue with incremental changes using the same entity mapping.
- Parallel snapshot partitions
- Target writing concurrency
- Bulk ingestion for large tables
03
Resilient delivery
Keep capture and delivery decoupled so temporary outages do not require a full reload.
- Persistent source-side queues
- Automatic reconnection
- Per-entity monitoring and control
FAQ
Frequently asked questions
Answers about log-based capture, initial snapshots, resilient delivery, and CDC targets.
What is change data capture streaming?
Change data capture streaming reads committed inserts, updates, and deletes from a database change stream and delivers them continuously to downstream systems.
Does Gluesync CDC repeatedly scan source tables?
No. Supported source agents read transaction logs, journals, or native CDC APIs instead of repeatedly polling full tables.
How does Gluesync handle the initial data load?
Gluesync can seed a target with a parallel snapshot and then continue with incremental changes using the same entity mapping.
What happens if a target or network path is unavailable?
Persistent source-side queues keep capture and delivery decoupled so the pipeline can reconnect and resume from acknowledged progress after a temporary interruption.
Where can CDC changes be delivered?
Gluesync can deliver captured changes to supported databases, event streams, cloud warehouses, object storage, and other data-platform targets.
Replace batch windows with a continuous change stream
Start a Gluesync trial or talk with MOLO17 about CDC across your database, cloud, and event-streaming estate.