Graph Application Development
Graph application development tools sit above graph databases, providing technical teams with specialized frameworks, SDKs, and low-code engines to construct, operate, and maintain operational graph applications.
IDEs, workbenches, and no-code/low-code platforms simplify building, deploying, and managing graph-powered applications by turning graph models into workflows, consoles, and analytical workspaces teams use day to day.
This catalog focuses on current graph clients, query IDEs, application platforms, and graph-powered workbenches that operate on top of existing graph databases.
Our Sponsors
Memgraph
Diamond sponsor
Memgraph is a high-performance, in-memory graph database built for real-time AI context and graph analytics. It serves as the graph engine for GraphRAG pipelines, AI memory systems, and agentic workflows, delivering sub-millisecond multi-hop traversals with full provenance for systems that need structured, connected context alongside semantic search. The same architecture powers real-time graph analytics across fraud detection, network analysis, infrastructure monitoring, and other operational use cases.
Neo4j
Diamond sponsor
Neo4j is the knowledge layer for enterprise AI. Powered by the Neo4j Graph Intelligence Platform, Neo4j connects organizational data with humans and AI systems, surfacing not just relationships, but how and why they exist. The result is AI that is accurate, explainable, and governable. Built to integrate with everything. Proven by 84 of the Fortune 100 and supported by the world’s largest graph community, Neo4j helps organizations move AI from pilot to production.
Process Tempo
Gold sponsor
Process Tempo Jupiter is a low-code/no-code platform that specializes in building enteprise-ready graph solutions. Use Jupiter to build complete applications, graph visualizations, dashboards and workflows that complement your graph ecosystem. Built-in security, role-based access, audit logs, multi-modal support, and AI integration help turn connected data into governed business actions.
To be included in this catalog, an offering must meet all three of the following criteria:
- Graph-native application layer: The tool natively understands graph data models (LPG or RDF) and speaks graph query languages (Cypher/openCypher, Gremlin, SPARQL, or GQL), directly or under the hood, without replacing the underlying database as the system of record. This is what separates graph application tools from generic low-code platforms that happen to have a graph connector.
- Durable Application & Workflow Environment: The product provides a generally available environment for building and running ongoing graph applications, workbenches, query IDEs, or workflows. Static visualization libraries and database admin consoles do not qualify.
- Clear Deployment Model & Named Graph Backends: The offering has a documented deployment model (SaaS, cloud, on-prem, containers, or IDE extensions) and explicitly names its supported graph databases.
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The table summarizes these tools across key dimensions so you can quickly see where each product fits and which merit a deeper look.