Neo4j launches serverless graph analytics platform for all users
Neo4j has released Neo4j Aura Graph Analytics, a serverless graph analytics solution designed to operate across any data source without requiring extract, load, and transfer (ETL) processes.
The new offering reportedly enables a broader pool of users to conduct graph analytics, traditionally a specialist discipline, by eliminating the need for custom queries, ETL pipelines, or detailed knowledge of graph technologies. It supports integration with a wide range of database and cloud data warehouse providers including Oracle, Microsoft SQL, Databricks, Snowflake, Google BigQuery, and Microsoft OneLake, alongside compatibility with all major cloud environments.
Graph analytics is engineered to assist with decision-making in artificial intelligence (AI) applications by identifying patterns and connections in complex datasets. According to Neo4j, the technique delivers more accurate insights than conventional analytics, yet has often been perceived as accessible only to data scientists and advanced analytics practitioners.
Neo4j Aura Graph Analytics introduces more than 65 pre-built graph algorithms prepared for users who may not have prior experience with the Cypher query language or similar technologies. The company states that the product can be deployed and scaled without infrastructure setup, and is available on a pay-as-you-use model, allowing organisations to control costs according to their compute and storage requirements.
Neo4j refers to customer-reported benefits from early adopters, including up to 80% improvements in model accuracy and a doubling of insight efficacy compared to traditional analytics approaches.
The company attributes this to the use of graph embeddings that translate graph structures into features ready for machine learning workflows, providing enhanced ability to detect subtle relationships and patterns in data.
Various use cases are cited for the technology, including anti-money laundering, fraud detection, disease contact tracing, supply chain management, customer 360 initiatives, recommendation engines, and social network analysis. Neo4j notes that the system supports highly parallelised in-memory processing, enabling analytics to be conducted twice as fast as some open-source alternatives, and allows for unlimited concurrent sessions by different organisational users.
The platform is accessible directly via Python, and users can exploit familiar tools such as Pandas dataframes to project, analyse, and visualise enterprise data without additional ETL requirements. Neo4j reports a 75% reduction in required coding as the solution removes the need to manually build models for each new analysis. The serverless model absolves the organisation of infrastructure administration, with users only paying for resources used.
Support for other widely-used programming languages is planned for later in the year, with a specific native integration for Snowflake expected to become generally available by the third quarter of the financial year. Neo4j's expansion of its analytical capabilities with serverless deployments is a response to increased demand for AI-ready and analytical solutions, according to the company.
Neo4j has reported a series of milestones, including an upgrade to its Aura cloud management system with AI features in September 2024, its recognition as a Visionary in the 2024 Gartner Magic Quadrant for Cloud Database Management Systems for the second straight year, and designation as a Strong Performer in the Forrester Wave: Vector Databases, Q3 2024. In November 2024, Neo4j announced that it had doubled its annual recurring revenue over three years, reaching a valuation above USD $2 billion, and noted usage by a significant proportion of Fortune 100 and Fortune 500 companies.
The role of graph analytics in enterprise data management was also noted in industry research, with Gartner indicating: "Data captured in any enterprise is sparse and replete with gaps, making it difficult to find and link useful data. Data and analytics leaders should use graph analytics as a preferred technology in specific use cases to fill data gaps and blend data assets even when they have diverse data quality."
Devin Pratt, Research Director for Data Management at IDC, said: "Neo4j's new serverless graph analytics solution, developed with ease-of-use and accessibility in mind, is an exciting move that will allow enterprises to scale analytics across any data source or cloud platform, transforming their data into a wealth of actionable knowledge, and providing deeper insights for improved organizational decision-making."
Sudhir Hasbe, Chief Product Officer at Neo4j, commented: "Our vision with Aura Graph Analytics is simple: make it easy for any user to make better business decisions faster. By removing hurdles like complex queries, ETL and costly infrastructure set-up, organizations can tap into the full power of graph analytics without needing to be graph experts. The result: better decisions on any enterprise data source, built on a deeper understanding of how everything connects."
Neo4j reported customer benchmark data showing Neo4j Aura Graph Analytics delivers a 50–80% increase in accuracy for data science and machine learning models versus non-graph analytics, with this improvement leading to twice the efficacy in overall insights. The solution is available now under a pay-as-you-use plan and will continue to expand its integrations and supported languages in the coming year.
