Canonical: https://molo17.com/solutions/cdc-streaming/ Markdown mirror: https://molo17.com/solutions/cdc-streaming/index.md Title: CDC Streaming solution · Gluesync · MOLO17 Description: Capture committed database changes from transaction logs and deliver them continuously to databases, event streams, and data platforms—without polling full tables. 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. [Explore CDC streaming](#how-it-works) [Talk to our team](/contacts/?topic=data-architecture) 1. 01 Read the native change stream 2. 02 Buffer and route through Core Hub 3. 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. 01 / Latency ### Data arrives too late Periodic jobs leave applications and analytics working from an increasingly stale view of operational data. 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. 1. 01 Capture ### Read the native change stream Source agents read transaction logs, journals, or native CDC APIs instead of repeatedly scanning tables. 2. 02 Coordinate ### Buffer and route through Core Hub Durable local queues and pipeline state preserve events while a target or network path is unavailable. 3. 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 [Gluesync architecture](https://docs.molo17.com/gluesync/latest/introduction/architecture.html) 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 [Snapshot tasks](https://docs.molo17.com/gluesync/latest/core-hub/snapshot-tasks.html) 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 [Deployment best practices](https://docs.molo17.com/gluesync/latest/deploy-and-run/best-practices.html) Related solutions ## Continue exploring Gluesync use cases [ Solution · Modernization ### Cloud Migration Move large operational datasets with parallel snapshots, then keep source and cloud targets aligned with CDC until your applications are ready to switch. Explore Cloud Migration →](/solutions/cloud-migration/)[ Solution · Analytics delivery ### Warehouse Sync Stream operational changes into Snowflake, BigQuery, object storage, and other analytical targets using snapshots, CDC, and destination-native bulk loading. Explore Warehouse Sync →](/solutions/warehouse-sync/)[ Solution · Federated data access ### Federated Queries Run read-only SQL across isolated Gluesync agents through one JDBC endpoint—without first copying raw data into a central warehouse. Explore Federated Queries →](/solutions/federated-queries/) 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. [Request a free trial](/get-gluesync/) [Talk to our team](/contacts/?topic=data-architecture)