The persistence tax: Why it’s time to let your graph analytics sleep
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Mastering highly distributed architecture
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Powering recommendations with a graph database: Proven business benefits [+ case studies]
6 min read
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Products
- FULLY-MANAGED
- AuraDB Store and query connected data at scale
- Virtual Graph Create and query a knowledge graph on existing data
- Aura Graph Analytics Run graph algorithms on any data, any cloud
- Aura Agent Build and deploy context-aware agents fast
- SELF-MANAGED
- Graph Database Store connected data with a graph database
- Graph Data Science Run graph algorithms on connected data
- Bloom Securely query, explore, and visualize data
- Fleet Manager Manage all your Neo4j deployments from one place
- AI CAPABILITIES
- Knowledge layer
- AI systems
- GraphRAG
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Solutions
- INDUSTRIES
- Financial services
- Healthcare & life sciences
- Retail
- Telecommunications
- US federal government
- TECHNICAL PATTERNS
- Digital twin
- Knowledge graphs
- Metadata management
- Pattern matching
- USE CASES
- AI systems
- Customer experiences
- Data privacy, risk, & compliance
- Fraud
- Identify & access management
- Network & IT
- Real-time recommendations
- Supply chain
- PARTNERS
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Developers
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- DEV RESOURCES
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- BUILD WITH AI
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Resources
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- Video hub Covering graph databases, data science, analytics, and AI
- FEATURED EVENTS
- GraphSummit 2026 Graphs + AI: Transform your data into knowledge
- NODES 2026 | November 12 Virtual Conference: Engineering better intelligence
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