Ultipa Launches New Cloud Platform Featuring the First ISO GQL-Native Graph Database
April 1, 2026
Today we're excited to release a brand new version of Ultipa Cloud, a fully-managed Database-as-a-Service platform for GQLDB, our next-generation graph database engine (v6).
The graph database landscape has long been fragmented by proprietary query languages, forcing teams to learn vendor-specific syntax and making it difficult to switch providers or share expertise across organizations. The ISO/IEC 39075 GQL standard changes that, establishing a universal query language for graph databases, much like SQL did for relational databases decades ago.
GQLDB is the first graph database built from the ground up for this standard. It delivers a complete, self-contained graph database engine that is simple to deploy and operate - no complex dependencies or infrastructure to manage. With Ultipa Cloud, getting started only takes a few minutes.
What Makes GQLDB Different
Full ISO GQL Compliance. GQLDB implements the GQL standard comprehensively, not as a partial overlay on a proprietary language. Pattern matching, variable-length paths, shortest/cheapest path queries, and query composition all 100% follow the ISO specification. Teams learn one standard query language that works across any future GQL-compliant system.
Purpose-Built Storage Engine. GQLDB uses its own storage engine designed specifically for graph data. Edges are stored so that finding a node's neighbors is an instant lookup rather than a search, delivering consistent performance even as your data grows to millions of nodes and edges.
Compiled Stored Procedures. Complex graph logic can be written as stored procedures that are compiled into optimized bytecode, not interpreted at runtime. This includes support for parallel graph traversal across CPU cores and built-in algorithms like PageRank and Label Propagation - all running directly inside the database engine for maximum performance.
Native Vector Search. Vector similarity search is built into the query engine, not a separate add-on. Combine graph traversal with vector similarity in a single query - ideal for AI applications, semantic search, and retrieval-augmented generation (RAG).
Ontology & Semantic Layer. Model your domain with a built-in ontology layer compatible with OWL 2 RL. Load ontologies from RDF formats, enforce data constraints, and query across class hierarchies automatically - a natural fit for knowledge graphs in healthcare, finance, and research.
Intelligent Query Caching. Three layers of caching - parsed queries, execution plans, and query results - work together to deliver sub-millisecond response times on repeated queries, with automatic invalidation when your data changes.
Ultipa Cloud Platform
Building and operating a graph database in production requires more than just the database engine. Teams need provisioning, monitoring, backups, security, and scaling... all of which distract from the actual work of building applications. Ultipa Cloud handles all of this, so you can focus on your data and your queries.
Instant provisioning: get started with a free trial, no credit card required
Multi-region availability: US (N. Virginia), Europe (Frankfurt, Milan)
Flexible scaling: multiple instance sizes with configurable CPU, memory, and storage
Automated operations: scheduled backups, one-click restores, version upgrades, and self-healing recovery
Enterprise security: IP allowlisting, scoped API keys, role-based access control, and encrypted data at rest
Real-time observability: built-in monitoring with configurable alerts
Pay-as-you-go billing: transparent per-hour pricing with no long-term commitments
Ultipa Cloud Dashboard
Who Is This For
Ultipa Cloud and GQLDB are designed for teams building applications where relationships between data are as important as the data itself:
Knowledge graphs — model complex domains with ontology support and semantic inference, from enterprise knowledge management to biomedical research
Fraud detection — traverse transaction networks in real time to identify suspicious patterns, using compiled stored procedures for complex detection logic
Recommendation engines — combine graph traversal with vector similarity to deliver recommendations that account for both structural relationships and content similarity
RAG applications — power retrieval-augmented generation pipelines with native vector search over knowledge graphs, combining semantic retrieval with structured graph context
Network analysis — analyze infrastructure, social, or supply chain networks using built-in graph algorithms and parallel traversal
Regulatory compliance — leverage the ISO GQL standard and ontology validation for applications where standards compliance and data governance are requirements
Get Started Today
Ultipa Cloud is available now. Sign up for a free trial and deploy your first GQLDB instance in minutes. No credit card required, no infrastructure to manage. Experience the power of the first ISO GQL-native graph database, fully managed in the cloud.