Data Infrastructure Is Overdue for a Rethink
Applications today demand databases that handle wildly diverse workloads: real-time analytics, transactional consistency, graph traversals, and full-text search, often within the same system. xDB is engineered from the ground up to meet these demands without compromise.
Core Design Principles
Optimizes storage layout for your actual query patterns automatically.
Automatic sharding and live rebalancing as your cluster grows.
Documents, key-value, graph, and time-series in one unified system.
From eventual to strict serializable — per-operation control.
Native similarity search for AI embeddings and RAG workloads.
Online schema evolution without maintenance windows.
Performance Without Tradeoffs
Traditional databases force you to choose between consistency and speed, flexibility and performance. xDB uses a novel architecture that adapts its storage and indexing strategies based on workload analysis, delivering optimal performance across mixed use cases.
Built for Operators
A fast database that is painful to operate is not a good database. xDB prioritizes operational simplicity with automated backups, point-in-time recovery, rolling upgrades, and deep observability out of the box.
Multi-Model Query Example
// Single query spanning multiple models
result := xdb.Query().
From("users"). // document model
Join("sessions", "user_id"). // key-value model
Graph("friends", depth=2). // graph traversal
VectorSim(embedding, k=10). // vector search
Consistency(Linearizable).
Run(ctx)Early Access
xDB is in its engineering phase. We are looking for teams with demanding data workloads to join our early access program and help shape the platform. Contact us below to learn more.