Databases for production workloads
Operate relational, document, and caching layers with managed backups, high availability, read scaling, performance visibility, and secure access patterns.
Deployment blueprint
What teams get on day one
Multiple database engines
Run relational, key-value, and document stores from one platform while preserving engine-specific tuning and lifecycle controls.
Automated backups with recovery paths
Keep daily and point-in-time recovery options available without requiring teams to maintain bespoke backup scripts.
High-availability topologies
Use managed failover and replicated deployments to keep critical services available during infrastructure or node failures.
99.99%
HA target
PITR
recovery support
Read
replica scaling
Multi-engine
operational coverage
Core capabilities
Purpose-built for modern engineering teams
Multiple database engines
Run relational, key-value, and document stores from one platform while preserving engine-specific tuning and lifecycle controls.
Automated backups with recovery paths
Keep daily and point-in-time recovery options available without requiring teams to maintain bespoke backup scripts.
High-availability topologies
Use managed failover and replicated deployments to keep critical services available during infrastructure or node failures.
Read scaling for growth
Add replicas for analytical, search, or read-heavy application patterns without overloading primary write nodes.
Query and performance monitoring
Inspect latency, throughput, slow queries, and resource pressure before small regressions become customer-visible outages.
Secure connectivity by default
Use encrypted traffic, scoped credentials, network isolation, and role-based access as the standard database operating model.
Delivery flow
How teams adopt databases
The platform is designed to reduce setup friction, standardize delivery, and give every team a clear operating model from day one.
Provision the right engine profile
Choose capacity, availability zones, backup windows, and access policies based on workload shape and business criticality.
Monitor health and usage over time
Track performance, replica lag, storage growth, and connection behavior from the same operator dashboard.
Scale or recover without service chaos
Expand capacity, add replicas, or restore data with guided workflows that minimize downstream application disruption.
Use cases
High-impact scenarios teams run on VxCloud
SaaS application backends
Support customer-facing APIs with managed relational data services that reduce routine operational burden.
Caching and event-heavy systems
Pair primary databases with fast in-memory layers for latency-sensitive applications and bursty workloads.
Analytics-ready read paths
Send reporting and read-heavy jobs to replicas so transaction-serving paths remain predictable.
Integrates with your existing stack
Bring current tooling forward instead of rebuilding workflows. Standard integrations are available immediately, with deeper automation on top.
Operator outcome
Teams get a sharper developer loop, stronger governance, and a cleaner production handoff without adding separate point tools to manage.
Build the next workflow on top of Databases
Start in minutes with VxCloud-managed infrastructure, AI-assisted setup, and a production-ready baseline your team can extend safely.