Database engineering across relational, distributed, and mainframe estates.

Relational engines

Deep expertise across PostgreSQL, Oracle, IBM DB2, Microsoft SQL Server, and MariaDB. We handle schema design, index strategy, query plan analysis, ACID lock contention, replication topology, and the long tail of edge cases that only reveal themselves under production load.

Distributed state fabrics

Redis Cluster, Hazelcast IMDG, and MongoDB replica sets for workloads that outgrow a single relational engine. We work on the actual topology — sharding, consistency modes, failover behaviour — rather than treating the cache layer as a magic performance box.

Mainframe and heritage data

Decades-old Adabas and other mainframe estates don't go away just because your front-end did. We extract, modernise, and bridge heritage data stores into modern pipelines without disrupting the mainframe workloads that still run beneath them.

Integrity and disaster recovery

Continuous log shipping

Write-ahead logs are shipped continuously to a secondary site. Recovery is a known procedure with a documented runbook, not an improvisation during an outage.

4-hour RTO / RPO targets

For mission-critical ERP and transactional databases we target a 4-hour recovery time objective and a comparable recovery point objective. Specific commitments depend on the stack and traffic profile — we agree them in writing before contract.

Verified test restores

Backups you never restore are rumours, not backups. We restore to a sandbox on a regular schedule and verify the data against production checksums, so the recovery procedure is proven to work before you need it.