Neo4j Consulting
We help enterprises develop knowledge bases, architect business solutions on top of Neo4j, design intelligence platforms and all that is required on the way to graph success.
Neo4j Graph Database
At the core of the Neo4j Graph Data Platform is the Neo4j Graph Database, a native graph data store built from the ground up, to leverage not only data but also data relationships. Unlike other types of databases, Neo4j connects data as it’s stored, enabling queries never before imagined, at speeds never thought possible.
This speed and efficiency advantage of the Neo4j Graph Database has driven dozens of business game-changing use cases in fraud detection, financial services, life sciences, data science, knowledge graphs and more. Because of this, graph databases have become a key technology in creating competitive advantage for hundreds of Fortune 500 companies, government agencies and NGOs.
There are many ways to deploy Neo4j today: on-premise server installation, self-hosted in the cloud with pre-built images, or by simply using Aura Cloud, the zero-admin, always-on graph database for cloud developers.
Graph Data Science Library
The Neo4j Graph Data Science Library uses the graph structure in data to help data scientists address complex questions about system dynamics and group behavior.
Businesses use these insights to make valuable predictions, such as pinpointing interactions that indicate fraud, identifying similar entities or individuals, finding the most influential elements in patient or customer journeys, and how to minimize the impact of IT, phone or other network outages.
There are many ways to deploy Neo4j today: on-premise server installation, self-hosted in the cloud with pre-built images, or by simply using Aura, the zero-admin, always-on graph database for cloud developers.
The GDS Library makes addressing these questions feasible. Data scientists benefit from a customized, flexible data structure for global computations and a repository of powerful, robust graph algorithms to quickly compute results over tens of billions of nodes.
Graph algorithms provide unsupervised machine learning (ML) methods and heuristics that learn and describe the topology of your graph. The GDS Library includes hardened graph algorithms with enterprise features, like deterministic seeding for consistent results and reproducible ML workflows.
The Cypher Query Language
With Neo4j, connections between data are stored – not computed at query time. Cypher is a powerful, graph-optimized query language that understands, and takes advantage of, these stored connections.
Cypher is inspired by SQL, with the addition of pattern matching borrowed from SPARQL. It uses simple ASCII symbols to represent nodes and relationships, making queries easy to read and understand.
Cypher queries are usually much simpler and easier to write than an equivalent SQL query. Because Neo4j doesn’t have tables, there are no JOINs to deal with, and a simple Cypher statement often takes the place of many lines of SQL code.
Because Cypher queries tend to be much shorter and simpler than similar SQL queries, Cypher code is easier to maintain, simplifying application maintenance.
Connectors & Integrations
Neo4j offers several connectors to facilitate use of Neo4j in your particular architecture, and provides instructional support for some third-party and community tools.
- The Neo4j Connector for Apache Spark is an integration tool that bidirectionally moves and reshapes data between the Neo4j graph platform and Apache Spark and opens up the vast Spark Ecosystem to Neo4j.
- The Neo4j Connector for Apache Kafka integrates Neo4j with Apache Kafka event streams, to serve as a source of data, for instance change data (CDC) or a sink to ingest any kind of Kafka event into your graph.
- Neo4j Connector for BI is a JDBC-compliant driver for third-party tools like Tableau, Looker, TIBCO Spotfire Server and Microstrategy. It allows those tools to execute SQL queries directly against a Neo4j server.
- The Neo4j Labs team is always innovating to bring useful graph technologies like the Neo4j ETL Tool and the GRANDstack development stack to the Neo4j community, as a way to test functionality and extensions of our product offerings. These Labs projects are supported via the online community.
