1000x Performance at Ultimate Graph-Native Scale
- 12600x performance gain at scale
- 18 million users receiving millions of alerts via activity feed
- 72% faster sign-up to initial activity
- 30 billion nodes, 67 billion properties, and 35 billion relationships
- 350 million user profiles optimized
- 612% increase in visits per day
“At albelli, we regularly deal with petabytes of data, and we are most excited about the new scalability features in Neo4j 4.0. The ability to horizontally scale with the new sharding and federation features, alongside Neo4j’s optimal scale-up architecture, will enable us to grow our graph database without barriers.”Josh Marcus, Chief Technology Officer, albelli
Bet365’s Risk Management Team quickly concluded that the technology would comfortably provide the scalability demanded by its applications for the foreseeable future. "Our graph is over 1.5 terabytes yet it is still extremely fast."Richard Burton, Head of Management Information Systems, Hillside Technology Ltd.
"Getting a competitive price for a plane journey involves a large amount of complex data processing that the traveler just never sees. So it’s a big job, and an important one. Just one of our many airline customers estimates that, every day, if you add up all the various markets, flights, seats, and options in what they put in the sky, it’s over 100 billion product permutations. “Neo4j has met the needs of our product teams and delighted our customers. It’s performant, scalable, and we expect it to continue to help us expose and build new airline data products and services.”Navid Abbassi, Chief Architect, ATPCO
"NASA has over 50 years of data, dating back to the Apollo and Gemini eras. Based on what I have seen, billions of nodes and relationships will not be an issue with Neo4j."David Meza, NASA
The Fastest Path to Graph Scaling and Flexible Development
Data grows relentlessly and performant applications can’t be constrained by data volumes. Applications need to scale up and scale out to handle higher data volumes, while also maintaining data integrity and performance across a growing diversity of on-premises, hybrid, and cloud architectures.
Neo4j’s high-performance distributed cluster architecture scales with your data and your business needs in real-world situations, minimizing cost and hardware while maximizing performance across connected datasets. With Neo4j, you can now achieve robust transactional guarantees, performance across billions of nodes, trillions of relationships with millisecond response time, and unlimited elasticity.
Neo4j’s schema-less data model provides an extremely valuable concept-first approach when working on building and evolving a data model for changing business requirements, enabling developer velocity.
Optimized for Lightspeed Throughput
Grow Your Database Without Barriers
Get reliably fast transactions with ultra-high parallelized throughput even as data grows because graph provides index-free adjacency; that shortens read time and gets even better as data complexity grows.
Neo4j’s distributed high-performance architecture is fault-tolerant and guarantees data integrity (ACID compliant) in all topologies ensuring safe scalability without having to compromise performance. The stateful, cluster-aware sessions with encrypted connections do not require load balancers to ensure all client requests are seamlessly redirected to the correct server.
Neo4j’s distributed architecture offers:
Continuous Availability for OLTP
- Faster failover times
- Guaranteed commit throughout the cluster when there is a majority (consensus commits)
- Core servers dedicated for write operations, and dedicated Read Replicas
- Geo distributed multi-datacenter deployments
Graph Data Science and Analytic Read Scaling
- Unlimited scale out for reads with a single-core server, unlimited multiple read replicas
Large scale hybrid clusters
- Virtually unlimited scale out for read and write intensive workloads using Neo4j Fabric
- Fabric provides sharding and federated capabilities both in local and geo distributed environments
You can further scale reads horizontally, meaning 1000x as many reads by simply adding more Read Replicas.
Limitless Horizontal Scaling
A large graph database may have a potentially unlimited number of nodes. So the ability to divide the graph database across many servers is key to scalability, as well as the ability to support use cases such as compliance with data privacy regulations.
Sharding is the division of a single logical database into as many physical machines as is required. With Neo4j, you can achieve unlimited horizontal scalability via sharding for mission-critical applications with a minutes-to-milliseconds performance advantage.
Multiple Business Graphs
While sharding divides graphs, federated graphs bring multiple graphs together, supporting queries across graph databases that may have different logical structures. Federation allows you to:
- Query against massive graphs that share a schema at global scale and distribution
- Query against different business graphs, an entirely new capability for the graph database world and unique to Neo4j
Sharding Graph Data with Neo4j Fabric
Scale and Reliability. Zero Compromise
Fabric provides unlimited scalability by simplifying the data model to reduce complexity. With Fabric, you can execute queries in parallel on multiple databases, combining or aggregating results. It also allows you to chain queries together from multiple databases for sophisticated, real-time analyses.
Fabric helps you achieve a number of benefits, such as:
- A unified view of local and distributed data, accessible via a single client connection and user session
- Increased scalability for read/write operations, data volume, and concurrency
- Predictable response time for queries executed during normal operations, a failover, or other infrastructure changes
- High Availability and no single point of failure for large data volume
There are two modes of operations in Fabric:
- Sharding: Operate over a single large graph
- Federation: Query across disjointed graphs
Neo4j enables organizations to slice their large-scale graph datasets into separate, smaller, and faster chunks (shards) and store them using our distributed sharding architecture across multiple systems. Though physical storage of a graph dataset is sharded across many servers or clusters, speed, consistency, and data integrity are maintained.
Shard a graph to:
- Isolate data for compliance regulations like GDPR
- Minimize latency of queries in various regions by storing segments closer to users
- Break up very large graphs (tens of billions of nodes) into smaller graphs, so that you can run on smaller-sized hardware, while maintaining the performance users want
While sharding divides graphs, federation enables queries across disjointed graphs by bringing multiple graphs together.
Imagine having graphs across your organization, from IT to finances, operations, sales, HR, marketing, manufacturing, and more. Neo4j leverages the power of Cypher, allowing developers to query across these graphs – even ones with different schemas – as if it was one large graph.
The result: All data stored across an enterprise's graph database ecosystem are now searchable with a single Cypher query – an entirely new and powerful capability for the graph database world.
Neo4j Is Everywhere
Embracing Lightspeed Adoption of Graphs
Neo4j is the fastest path to graph, and is the only enterprise-strength graph database that combines native graph storage, scalable architecture optimized for speed, and ACID compliance to ensure predictability of relationship-based queries.
Neo4j – the graph data platform market leader – powers more than 4,300 startups, 800 enterprises, 75% of the Fortune 500, and 200K+ developers, all while delivering the definitive foundation for connected data at unlimited scale and developer velocity. Neo4j is used by 7 of the world’s top 10 retailers, 3 of the top 5 aircraft manufacturers, 8 of the top 10 insurance companies, All of North America’s top 20 banks, 8 of the top 10 automakers, 3 of the world’s top 5 hotels, and 7 of the top 10 telcos.
Neo4j has been downloaded 2 million+ times and Docker pulled 144 million times, boasts 90% of the deployments in the cloud, and boasts a vibrant and active developer community with more than 72000+ meetups conducted.