01 / Contention
Reports slow the transactions
Analytical scans hold resources on the system of record precisely when operational load is at its highest.
Solution · Workload offloading
Move read traffic off the system of record
Replicate IBM i, Oracle, and other critical databases into read targets via journal/log CDC so reporting stops competing with transactions.
- 01 Read the native change source
- 02 Maintain a read-optimized copy
- 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.
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.
- 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.
- 02
Redirect
Maintain a read-optimized copy
Target agents keep a cache, distributed SQL store, or in-memory grid aligned with the source continuously.
- 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
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
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
FAQ
Frequently asked questions
Answers about low-impact capture, read replicas, target choices, and bounded delivery.
What is database workload offloading?
Database offloading maintains a current copy in a read-optimized target so reporting, APIs, or analytical queries no longer compete with transactions on the system of record.
How does Gluesync limit load on the source database?
Supported agents read native journals, transaction logs, or CDC interfaces instead of repeatedly polling full tables.
Which systems can receive an offloaded copy?
Depending on the workload, Gluesync can deliver to targets such as Redis, SingleStore, GridGain, cloud databases, and other supported engines.
Can the offload pipeline restrict what reaches the target?
Yes. Allowed-operation controls and inclusive row filters can bound the changes forwarded to the read target.
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.