Neo4j's suite of graph technology products
helps the world make sense of data.
Centered around the leading graph database, today's Neo4j Graph Data Platform is a suite of applications and tools helping the world make sense of data.
The Platform includes Neo4j Graph Data Science – the leading enterprise-ready analytics workspace for graph data – the graph visualization and exploration tool Bloom, the Cypher query language, and numerous tools, integrations and connectors to help developers and data scientists build graph-based solutions with ease.
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.
Neo4j's cloud service, AuraDB, is now available free for small projects, with no credit card required.
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 AuraDB, the zero-admin, always-on graph database for cloud developers.
Neo4j Graph Data Science is a software platform helping data scientists uncover the connections in big data to answer business critical questions and improve predictions.
Businesses use graph data science insights to pinpoint interactions that indicate fraud, identify similar entities or individuals, improve customer satisfaction through better recommendations, and optimize supply chains.
Neo4j Graph Data Science makes it easier to unlock answers because it puts relationships first, instead of keeping them hidden within rows and columns. Data scientists can analyze these relationships in a flexible workspace using a library of over 65+ pre-tuned algorithms, connected data techniques, and in-graph machine learning (ML) models. Its scalable infrastructure works with existing data science tools and workflows, so you can easily move from proof of concept to production.
The dedicated workspace integrates ingestion, analysis, and management to easily improve models without rebuilding their workflow. ML Ops allows data scientists to focus on extracting insights, training ML models, and deploying projects across production areas.
Neo4j Bloom is an easy-to-use graph exploration application for visually interacting with Neo4j graphs. Bloom gives graph novices and experts alike the ability to visually investigate and explore graph data from different business perspectives.
Bloom’s illustrative, codeless search-to-visualization design makes it the ideal interface for fostering communication between peers, managers and executives, and sharing the work of graph development and analytics teams.
Bloom is used across a number of industries and use cases, from accelerating scientists’ understanding of disease pathways to data scientists and investigators working together on predictive fraud models.
In the realm of graph data science, Bloom enables data scientists to follow their intuition in exploring interesting patterns, visualizing algorithm results and streamlining conversations with subject matter experts.
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.
Neo4j offers several connectors to facilitate use of Neo4j in your particular architecture, and provides instructional support for some third-party and community tools.
Neo4j provides sophisticated tools designed to make it easier to develop graph applications.
Neo4j is a cloud-friendly database, with a variety of cloud deployment options readily available. Over 50 percent of Neo4j customers run Neo4j in the cloud today on public clouds like AWS, Azure and Google Cloud Platform (GCP). Of course, Neo4j also runs on-prem, in private clouds or in hybrid environments.
Neo4j AuraDB is Neo4j’s fully managed cloud service – the zero-admin, always-on graph database for cloud developers. It’s available today for free directly from Neo4j, with no credit card required. AuraDB is also on Google Cloud Platform and AWS.
AuraDB lets you focus on what’s important – developing rich, graph-powered applications – without the hassle of managing infrastructure.
With a simple pricing structure based on hourly billing, and rates starting as low as 9 cents an hour, costs are always predictable. With on-demand scaling, automatic backups, self-healing infrastructure and world-class security, AuraDB is the easiest way to use Neo4j.
Neo4j AuraDS is the power of Neo4j Graph Data Science available as a fully managed cloud service. It includes access to over 65+ graph algorithms in a single workspace that empowers data scientists to experiment faster. In-graph ML models and the native Python client help increase productivity, as well as simplify workflows.
Quickly transform your data into a graph and begin analysis with AuraDS. Features include a drag-and-drop UI to model and import data into a graph, one-click backup, ML Ops support, automated workload management, and pay-as-you-go pricing for easy budget management. Available on Google Cloud Platform, you can pay with existing Google Cloud commitments or with a credit card.
Companies like HP, Neoris and many others embed Neo4j into their mission-critical software and applications. That's because Neo4j has a variety of drivers and APIs to extend the database into other applications.
Neo4j multi-database functionality allows organizations to leverage Neo4j’s power graph database for SaaS applications. Neo4j can be embedded into SaaS applications as a powerful database to store and analyze data.