Migrations
Migrations designed, moved and run by the team that supports the result
Last reviewed by Tyler Eastridge
AceMQ assesses your current platform, plans the move, rehearses it on a copy of your data and cuts over with a tested rollback plan. Then we run the new platform under 24/7 support or as a managed service, so the engineers who moved it are the ones on call afterwards. Our database migration services cover the migration assessment, migration planning, data integrity checks and post-migration support, including moves to a cloud database such as Aurora PostgreSQL.
160+ customers10+ years15-min Sev 1 responseQuotes in 1 hour
- A rollback plan, tested in rehearsal
- A parallel run wherever the data allows it
- Data validation: row counts, checksums and app checks
- A runbook your team keeps
- 24/7 engineers on the line through cut-over
Routes
Pick your migration route
Each route links to the guide or service page that covers it in depth. If your route is not listed, ask and we will scope it.
Databases
- OraclePostgreSQL
Schema and PL/SQL conversion, data movement and the application SQL that has to change with it.
Service pageView service - SQL ServerPostgreSQL
T-SQL and data type mapping, agent jobs and a cut-over that fits your maintenance window.
Service pageView service - MySQLPostgreSQL
An engine move with replication into PostgreSQL and a parallel run before the switch.
Service pageView service - MySQLPostgreSQL
The step-by-step guide: type mapping, pgloader, AWS DMS or Debezium CDC, and the checks before cut-over.
GuideRead the guide - PostgreSQLAmazon Aurora
A compatibility check first, then AWS DMS or logical replication for the move.
On this pageSee below - RedisValkey
A stay-or-move review, compatibility tests against your clients and commands, then a rehearsed cut-over.
Service pageView service
Messaging & streaming
- Confluent PlatformApache Kafka
Brokers, Connect, Schema Registry and clients moved onto open-source Kafka.
Service pageView service - IBM MQRabbitMQ or Kafka
Queue managers and channels mapped workload by workload, with bridges and a parallel run during the move.
Service pageView service - ActiveMQ, SQS or MSMQRabbitMQ
Protocol and semantic mapping, dual-publish cut-over and evidence before the old broker is retired.
Service pageView service - TIBCO EMSRabbitMQ or Kafka
Queues, topics and the applications behind them, re-pointed in waves.
Solution pageHow we approach it
Search & data platforms
- ElasticsearchOpenSearch
Indices, mappings, client libraries and dashboards moved with a snapshot or reindex plan.
GuideRead the guide - Hadoop or ClouderaDatabricks
Data, jobs, SQL and permissions moved onto Databricks, each workload run in parallel until the numbers match.
Service pageView service - Legacy messaging modernization
The wider programme: which brokers to keep, which to retire, and the order to move them in.
Solution pageRead more
PostgreSQL to Aurora
Moving PostgreSQL to Amazon Aurora
Aurora PostgreSQL speaks the PostgreSQL protocol, but it is not the same engine underneath. We check what will not carry over, choose the move method that fits your downtime budget, and validate the data before the switch.
1. Compatibility check
Extensions, versions and parameters Aurora does not allow, superuser-only features, replication slots your applications rely on, and how Aurora's storage and I/O pricing will treat your workload.
If Aurora is the wrong target, we say so before you start.
2. Move method
- AWS DMS: full load plus change data capture
- Native logical replication for a short cut-over
- Dump and restore for small databases with a maintenance window
3. Cut-over and checks
Row counts, checksums and application checks on both sides, then the switch, with the source kept as the rollback target until you sign off.
How we migrate
Assess, plan, rehearse, cut over, run
The same five stages on every route. Nothing moves in production until the rehearsal has been timed and the rollback has been tested.
Assess
Schemas, code, integrations, data volumes and the SLAs the move has to keep.
Out: risk-ranked findings
Plan
Target design, conversion approach, cut-over method and the rollback plan.
Out: migration runbook
Rehearse
Full dry runs on a copy of production data, timed, until cut-over fits the window.
Out: measured cut-over time
Cut over
The move itself, with go and no-go checkpoints and engineers on the line.
Out: validated target
Run
24/7 support or managed operations on the new platform from day one.
Out: the same team on call
Rollback plan
Written in planning and tested in rehearsal. If a go or no-go check fails, the source stays primary and nothing is lost.
Parallel run
Where the data allows, old and new run side by side through replication or dual writes until their results match.
Data validation
Row counts, checksums and application-level checks on both sides, before and after cut-over.
Planning
Routes and what sets the pace
What each route has to move, and what decides how long it takes. The assessment turns this into a real plan and timeline for your estate.
| Route | What moves | What sets the pace |
|---|---|---|
| Oracle to PostgreSQL | Schema, PL/SQL, data, application SQL | How much PL/SQL and Oracle-only features you use |
| SQL Server to PostgreSQL | Schema, T-SQL, data, agent and SSIS jobs | Stored procedures and scheduled jobs |
| MySQL to PostgreSQL | Schema, data, application queries | Dialect differences in application code |
| PostgreSQL to Aurora | Data, extensions, parameters | Extensions in use and the downtime budget |
| Redis to Valkey | Data, configuration, clients | Modules and commands your clients depend on |
| Confluent Platform to Apache Kafka | Brokers, Connect, Schema Registry, clients | Confluent-only components in use |
| Elasticsearch to OpenSearch | Indices, mappings, clients, dashboards | Client libraries and plugins |
| IBM MQ or TIBCO EMS to RabbitMQ or Kafka | Queues, topics, applications, integrations | Number of applications to re-point |
| Hadoop or Cloudera to Databricks | Data, jobs, SQL, permissions | Job count and how much has to be rewritten |
Get a quote
Tell us where you are and where you want to land
Send the source, the target and what the platform carries. An engineer replies with an assessment plan and a quote.
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