No DBA on the team
Developers are carrying database operations alongside product work, and patching, tuning and backup verification keep slipping.
NubesDatabase runs your relational and NoSQL databases as a managed service: multi-AZ high availability, automated backups and patching, performance tuning and 24/7 monitoring.
Databases are where most production incidents start and where the least redundancy usually exists. Patching gets deferred because it needs a maintenance window, failover has never been tested, backups are configured but never restored, and query performance degrades slowly until something times out under load.
NubesDatabase takes that operational burden off your team. We design the topology, migrate you onto managed platforms where it makes sense, and then run it — patching, backups, failover testing, capacity and query tuning — against defined availability targets.
Multi-AZ with synchronous replication, and scheduled failover tests so you know the measured recovery time instead of trusting the documentation.
Security patches and minor version upgrades applied in agreed windows, with a tested rollback path and no surprise weekend work for your team.
Slow query analysis, index and parameter review and connection pooling done continuously, which is what stops the gradual slide into timeouts.
Encryption, rotated secrets, audit logging and least-privilege access configured as standard and documented for audits and customer questionnaires.
Audit engines, versions, sizing, backup and recovery posture, query performance and availability configuration. Output: a prioritised risk and improvement list.
Choose platform and engine, define the HA and replica topology, set backup and retention policy, and agree availability and performance targets.
Move onto managed platforms using continuous replication, validate with row counts and checksums, and cut over inside a short agreed window.
Monitor, patch, back up, test restores and failover, tune queries and capacity, and report against the agreed targets each month.
Developers are carrying database operations alongside product work, and patching, tuning and backup verification keep slipping.
Databases on EC2 or VMs that need to move to a managed platform to cut operational load and improve availability.
Commercial licensing costs are driving a move to PostgreSQL or MySQL, and the schema and application changes need planning and testing.
Relational engines including PostgreSQL, MySQL, MariaDB, SQL Server and Oracle, on managed platforms such as Amazon RDS and Aurora, Azure Database and Cloud SQL. On the NoSQL side we run DynamoDB, MongoDB-compatible services, Redis and Valkey caches, and we support self-managed engines where a managed platform does not fit.
Usually minutes. Log-based continuous replication keeps the target in sync while the source stays live, so cutover is a short window to drain connections, verify the final delta and repoint the application. Engines without replication support use a backup-and-restore window we schedule with you.
Multi-AZ deployments with synchronous replication and automated failover typically deliver 99.95% or better, with failover measured in tens of seconds. Adding read replicas and cross-region standbys raises resilience further. We agree the target per database and report against it, rather than quoting a single number for everything.
Automated daily backups plus continuous transaction log capture give point-in-time recovery, typically to any second within the retention window. Critically, we run periodic restore tests, because a backup that has never been restored is an assumption rather than a control.
Yes. Engine migrations to PostgreSQL or MySQL are common and usually licence-driven. We assess schema and code compatibility, convert what can be automated, plan the manual remediation for stored procedures and proprietary features, and run parallel validation before cutover.
Yes. Slow query analysis, execution plan review, index design, parameter tuning and connection pooling are part of the service. Where a problem is genuinely in application code or data model design, we identify it and work with your developers rather than masking it with a bigger instance.
Tell us which engines you run and where it hurts. We will review your availability, backup and performance posture and come back with a prioritised plan.
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