Assess before you move
We inventory schemas, dependencies, features in use, data volumes and performance baselines, and flag anything that will not translate cleanly.
Move to the cloud, to a new engine or to a new version without a weekend of downtime. We plan, rehearse and run database migrations so the cutover is the least exciting part.
Five stages, each with a clear exit criterion.
Inventory, compatibility and performance baseline.
Target architecture, sizing and conversion plan.
Initial load plus continuous change data capture.
Rehearsed switch with a tested rollback.
Tune on the new platform, then retire the old one.
Teams usually come to us in one of these situations.
Teams moving from SQL Server or Oracle to open-source engines.
On-premises databases heading to RDS, Aurora, Azure SQL or Cloud SQL.
Databases running versions that are out of support.
Move self-hosted databases to RDS, Aurora, Azure SQL or Cloud SQL.
Commercial to open source, for example SQL Server to PostgreSQL.
Major upgrades with compatibility testing and plan checks.
Merge sprawling instances into a smaller, cheaper estate.
We run the cutover end to end in a rehearsal environment first, timing every step, so the real switch is predictable.

Real problems we are asked to fix, what we do about them and the result to expect.
The situation
We assess which databases can move to PostgreSQL or MySQL, convert schemas and code, and plan a phased move with tests at each stage.
Licence savings without a risky big bang
The situation
We replicate continuously into RDS, Aurora, Azure SQL or Cloud SQL and cut over in a short, rehearsed window.
Cloud migration with minutes of downtime
The situation
We plan the upgrade path, test applications on the new version and complete the move well ahead of the deadline.
Supported, patched and secure again
The situation
We review what went wrong, add data verification and rollback steps, and rehearse the full cutover before touching production.
A migration plan you can trust
Replication-based cutovers measured in minutes.
Row counts, checksums and application tests before switching.
Licence savings and right-sized infrastructure after the move.
We inventory schemas, dependencies, features in use, data volumes and performance baselines, and flag anything that will not translate cleanly.
Continuous replication and change data capture keep the target in sync while applications are tested against it. The final switch takes minutes, not hours.
Row counts, checksums and application tests confirm the data, and performance is tuned on the new platform before the old one is retired.
Engine changes involve more than data: we convert schemas, stored procedures, functions and queries, and test them with your application before cutover.
We tune performance on the new platform, set up monitoring and backups, and keep the old system available until everyone is confident.
With replication-based migrations, the cutover window is usually minutes. The exact window depends on the engines, data volume and application behaviour, and is agreed in the plan.
Yes, for example SQL Server to PostgreSQL or MySQL to Aurora. Engine changes need schema and query conversion, which we scope and test carefully.
Every cutover has a rehearsed rollback plan, and the source stays available until the new platform is validated.
Simple version upgrades can take days; engine changes for large systems take weeks. The plan includes timings from a full rehearsal.
Moving engine versions rarely needs changes; moving between engines usually does. We identify every change during assessment.
Yes, including moves between self-hosted and managed services such as MongoDB Atlas and ClickHouse Cloud.
Request a scoped cloud assessment, or start with a free DevOps and SRE consultation. Talk to us about services, AI solutions or enterprise development.