Canonical: https://molo17.com/solutions/database-offload/ Markdown mirror: https://molo17.com/solutions/database-offload/index.md Title: Database Offload solution · Gluesync · MOLO17 Description: Replicate Db2 for IBM i, Oracle, and other mission-critical databases into read-optimized targets using journal and log-based capture, so reporting stops competing with transactions. Solution · Workload offloading # Move read traffic off the system of record Replicate Db2 for IBM i, Oracle, and other mission-critical databases into read-optimized targets using journal and log-based capture, so reporting stops competing with transactions. [Explore database offload](#how-it-works) [Talk to our team](/contacts/?topic=data-architecture) 1. 01 Read the native change source 2. 02 Maintain a read-optimized copy 3. 03 Keep the copy one-way The challenge ## Reads and transactions share one machine Reporting queries, APIs, and dashboards run against the same database that has to commit business transactions, and capacity is finite. 01 / Contention ### Reports slow the transactions Analytical scans hold resources on the system of record precisely when operational load is at its highest. 02 / Cost ### Scaling the core system is expensive Adding capacity to a licensed mission-critical platform just to serve read traffic is rarely the cheapest option. 03 / Shape ### Modern clients want other engines Applications expect caches, distributed SQL, or in-memory grids that the system of record was never designed to be. How it works ## Capture once, serve reads elsewhere Gluesync reads committed changes from the platform's native change mechanism and maintains a current read copy in whichever engine the consumers need. 1. 01 Capture ### Read the native change source Journal capture on Db2 for IBM i, LogMiner or XStream on Oracle, and log readers elsewhere keep source impact low. 2. 02 Redirect ### Maintain a read-optimized copy Target agents keep a cache, distributed SQL store, or in-memory grid aligned with the source continuously. 3. 03 Protect ### Keep the copy one-way Allowed-operations forwarding and row filters bound exactly what the offload target is permitted to receive. Gluesync capabilities ## Low-impact capture into read-friendly targets Pick the capture mechanism the source platform supports, then the target shape your consumers actually want. 01 ### Journal and log capture Read committed changes from the platform's own change mechanism instead of polling tables. - Db2 for IBM i journal capture - Oracle LogMiner and XStream - PostgreSQL, MySQL, and SQL Server log readers [IBM i journal capture](https://docs.molo17.com/gluesync/latest/agents/ibm-i-series-change-data-capture-journal.html) [Oracle LogMiner agent](https://docs.molo17.com/gluesync/latest/agents/oracle-logminer-intro.html) 02 ### Read-optimized targets Land the offloaded copy in the engine that serves the read workload best. - Redis for cached reads - SingleStore for analytical SQL - GridGain for in-memory access [Redis target](https://docs.molo17.com/gluesync/latest/agents/redis-intro.html) [SingleStore target](https://docs.molo17.com/gluesync/latest/agents/singlestore-intro.html) 03 ### Bounded, observable delivery Control which operations are forwarded and watch the offload pipeline like any other route. - Allowed-operations forwarding - Inclusive row-level filters - Prometheus metrics and alerts [Allowed operations forwarding](https://docs.molo17.com/gluesync/latest/core-hub/allowed-operations-forwarding.html) [Monitoring](https://docs.molo17.com/gluesync/latest/alerting-logging-monitoring/monitoring.html) Related solutions ## Continue exploring Gluesync use cases [ Solution · Real-time integration ### CDC Streaming 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 →](/solutions/cdc-streaming/)[ 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 · 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/) ## Let the system of record do transactions Talk with MOLO17 about capture on your source platform and the right read target, or start a Gluesync trial. [Request a free trial](/get-gluesync/) [Talk to our team](/contacts/?topic=data-architecture)