VectorX DB, the world's Most Secure, and High Performance Vector Database

Building and scaling a next-generation vector database requires more than speed and accuracy. It demands global reliability, enterprise-grade security, and the ability to integrate with AI workloads where they actually run. That’s why VectorX DB’s serverless platform is built natively on Google Cloud Platform (GCP).

By leveraging GCP’s compute, monitoring, and networking stack, VectorX DB ensures our customers benefit from a secure, scalable, and high-performance foundation while focusing on building GenAI and RAG applications.

Multi-Region Deployment on GCP

VectorX DB operates across multiple GCP regions, ensuring resilience and global reach:

Production Regions: India-West, US-West
Development Region: India-West

This multi-region approach allows us to meet client requirements across geographies while maintaining sub-10ms query latency and 99%+ recall accuracy at scale.

Inside the VectorX DB Architecture on GCP

At its core, our SaaS platform runs on Google Compute Engine, using high-performance c4-standard-32 VMs with 32 vCPUs and 120 GB of memory, optimized on Intel Emerald Rapids processors.

Each deployment integrates seamlessly with key GCP services:

Compute Engine: Hosts our application stack, APIs, and background jobs.
Cloud Operations (Ops Agent): Provides real-time system monitoring, log collection, and performance tracking.
VPC Network Services: Enforces firewall rules, port security, and regional traffic filtering for secure data flow.

This architecture ensures always-on observability, secure communication, and enterprise-grade reliability across all environments.

Why Google Cloud

We chose GCP not just for raw performance, but for the ecosystem it enables:

Scalability: Rapid vertical and horizontal scaling across regions.
Security: Native firewall rules, traffic controls, and monitoring.
Integration: Designed to interoperate with Vertex AI (for embedding generation) and BigQuery (for metadata analytics).

Future releases of VectorX DB will deepen this integration, making it seamless for customers to ingest embeddings from Vertex AI, store them securely in VectorX DB, and enrich results with BigQuery pipelines.

Deployment Snapshot

Component Purpose Implementation Compute Engine VMs Host applications and databasesc4-standard-32 instancesOps Agent Monitoring and logging Installed on all VMs VPC Firewall Rules Port and traffic management Enforced at region level Regional Distribution Global service deliveryIndia-West & US-West

The Outcome

By hosting VectorX DB directly on GCP, we’ve achieved:

High Performance: 1000+ queries per second, <10ms latency at P99.
Security: Queryable encryption across storage, memory, and transit.
Resilience: Multi-region deployment for enterprise workloads.
Future-Readiness: Built to integrate seamlessly with GCP AI/ML workflows.

Closing

At VectorX DB, we believe AI infrastructure should be secure by design and performance-driven at scale. By running our SaaS platform on Google Cloud, we give developers and enterprises the confidence to build advanced AI applications without worrying about infrastructure bottlenecks.