Migrate databases, data warehouses, and data lakes with replication, validation, and zero-data-loss cutover — across providers and formats.
Talk to a data engineerData migration is the riskiest part of any cloud project. Lose data and you lose customers, trust, and (in regulated industries) your license. Most data migrations fail because of poor validation — teams move the data, declare victory, and discover weeks later that 2% of records didn't make it, or that foreign keys are broken, or that the schema changed mid-migration.
CB4UHost migrates data with replication, validation, and zero-data-loss cutover. We use CDC (change data capture) for near-zero-downtime migrations, hash-based validation to prove row counts and checksums match, and tested cutover procedures that can roll back if validation fails.
We've migrated databases (MySQL, Postgres, SQL Server, Oracle, MongoDB, DynamoDB), data warehouses (Redshift, BigQuery, Snowflake, Synapse), and data lakes (S3, GCS, Azure Blob, HDFS). We handle cross-provider migrations (e.g. Oracle → Postgres) and cross-format migrations (e.g. relational → columnar).
Every migration ends with a validation report, a post-mortem, and a 30-day monitoring window to catch any issues.
We profile your schema, data volume, distribution, and dependencies before planning the migration.
Big-bang, CDC-based, or hybrid — chosen based on your downtime tolerance and data volume.
CDC replication for near-zero-downtime, with tested cutover procedure.
Row count, checksum, and business-rule validation to prove the migration succeeded.
Tested rollback procedure in case validation fails or issues surface post-cutover.
30-day monitoring for query performance, error rates, and data drift.
We profile the source data and design the migration strategy.
We migrate the schema (with transformations if cross-provider).
We set up CDC replication (or bulk load + delta sync) to copy data.
We validate, cutover, and validate again post-cutover.
We monitor for 30 days and hand over runbooks.
Interactive tools related to this service.
We use CDC (change data capture) tools like Debezium or AWS DMS to replicate changes from source to target in real-time. At cutover, we wait for replication to catch up, pause writes for seconds, switch the connection string, and resume. Total downtime: typically 30 seconds to 5 minutes.
Three layers: (1) row count comparison, (2) checksum/hash comparison on a sample of rows, (3) business-rule validation (e.g. 'sum of orders matches'). We report any discrepancies before declaring success.
Yes. We handle schema conversion, PL/SQL → PL/pgSQL, data type mapping, and query rewriting. Cross-engine migration is more work than same-engine, but we've done it many times.
We use tools like aws s3 sync, gsutil, or DistCp for bulk transfer, plus incremental sync for ongoing changes. For petabyte-scale migrations we use physical transfer (Snowball, Transfer Appliance) as a one-time bulk load.
Migrate VMs, storage, and networking from one provider to another — with zero-drama cutover, rollback, and post-migration optimization.
Move applications between clouds, providers, or architectures — with refactoring options from lift-and-shift to full replatforming.
DBA-as-a-service for MySQL, Postgres, SQL Server, MongoDB, and Redis — schema review, query tuning, backups, replication, and 24×7 monitoring.
Tell us about your project. We'll come back with a scoped proposal and a fixed-fee quote.
Talk to a data engineer