Serverless offering with 65+ ready-to-use algorithms boosts model accuracy by up to 80% and delivers 2X deeper insights - no graph expertise needed
SAN MATEO, Calif. , May 7, 2025 -- Neo4j®, the world's leading graph database and analytics company, announced the launch of Neo4j Aura Graph Analytics, a new serverless offering that for the first time can be used seamlessly with any data source, and with Zero ETL (extract, load, transfer). The solution delivers the power of graph analytics to users of all skill levels, unlocking deeper intelligence and achieving 2X* greater insight precision and quality over traditional analytics. Neo4j Aura Graph Analytics is generally available now on a pay-as-you-use basis and works with all databases, such as Oracle and Microsoft SQL, all cloud data warehouses and data lake platforms, such as Databricks, Snowflake, Google BigQuery, Microsoft OneLake, and on any cloud.
Graph analytics improves AI decision-making by uncovering hidden patterns and relationships in complex data, delivering more accurate insights with richer context than traditional analytics. Yet despite its powerful capabilities, graph analytics has remained out of reach for many organizations due to its complexity and learning curve – until now. The new Neo4j offering makes graph analytics capabilities accessible to everyone and eliminates adoption barriers by removing the need for custom queries, ETL pipelines, or any need for specialized graph expertise – so that business decision-makers, data scientists, and other users can focus on outcomes, not overhead.
"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," says Gartner in its Exploring the Top Use Cases for Graph Analytics report, May 10, 2024, by Jim Hare and Mark Beyer.
Neo4j Aura Graph Analytics requires no infrastructure setup and no prior experience with graph technology or Cypher query language. Users seamlessly deploy and scale graph analytics workloads end-to-end, enabling them to collect, organize, analyze, and visualize data. The offering includes the industry's largest selection of 65+ ready-to-use graph algorithms and is optimized for high-performance applications and parallel workflows. Users pay only for the processing power and storage they consume.
Additional benefits and capabilities below are based on customer-reported outcomes that reflect real-world performance gains:
- Up to 80% model accuracy, leading to 2X greater efficacy of insights that go beyond the limits of traditional analytics. Accuracy is achieved by transforming graph structures into ML-ready features with graph embeddings, unlocking graph's unique ability to uncover deeper patterns and relationships in complex connected data. Graph also dynamically aligns in real time as data changes, because it is driven by the connections between data points, not just the data itself. Advanced graph algorithms and embeddings, such as centrality, pathfinding, community detection, link prediction, and similarity, dramatically improve outcomes across hundreds of use cases such as fraud detection, anti-money laundering, disease contact tracing, customer 360, supply chain management, recommendation engines, and social network analysis.
- Insights achieved twice as fast as open-source alternatives with parallelized in-memory processing of graph algorithms. The offering's ability to run different yet simultaneous DSML (data science and machine learning) research instances also improves data analyst productivity. Users can scale graph analytics across their organization with unlimited concurrent sessions, each running independently.
- 75% less code, Zero ETL. Lower code is achieved by the ability to apply 65+ ready-to-use graph algorithms, eliminating the need to manually build models for each analysis. Users run the offering anywhere, directly on any enterprise data and in the data science environment most familiar to them by easily projecting data from Pandas dataframes, and with Zero-ETL. Users are also able to use the Python-based data science tools that they are already familiar with to project subgraphs, run algorithms, and return results.
- No administration overhead, and lower total cost of ownership. The fully managed serverless offering removes the burden of server provisioning, maintenance, or resource management. Users also minimize administrative costs and optimize infrastructure costs through a flexible pay-as-you-use service, scaling compute and storage up or down as needed for more precise spending control.
Neo4j Aura Graph Analytics is available for all data sources through Pandas dataframes in Python. According to GitHub, Python is the most commonly used language for AI. Support for all other major languages is expected this year.
Native integration with Snowflake to be generally available by Q3FY25
Neo4j Graph Analytics for Snowflake, a native integration with Snowflake, will be generally available this Q3 following its launch last year and numerous large-scale enterprise deployments. The move underscores mainstream demand for graph analytics across the most widely adopted data clouds, so that organizations across industries can operationalize data for faster and more accurate insights regardless of where that data lives. The offering can be purchased on Snowflake Marketplace.
Latest milestones driven by surging AI and graph demand
Neo4j's new serverless offering builds on a series of milestones for Neo4j. In September 2024, Neo4j transformed its Aura cloud database management system portfolio with AI-ready capabilities to simplify and accelerate graph adoption across any use case or workload. The result enabled Neo4j to advance its position as the category leader and the preferred graph partner across all major cloud service providers due to its comprehensive offering, deployment flexibility, analytics, and strong community support, accelerated with GenAI.
In December, the company was recognized as a Visionary in the 2024 Gartner® Magic Quadrant™ for Cloud Database Management Systems for the second consecutive year. Neo4j also ranked as a Strong Performer among 14 top vendors in The Forrester Wave™: Vector Databases, Q3 2024.
In November 2024, Neo4j doubled its annual recurring revenue in three years at a $2B+ valuation, driven by growing cloud adoption and GenAI demand. Neo4j is used by 84% of Fortune 100 companies and 58% of the Fortune 500, including Adobe, BT Group, Novo Nordisk, and UBS.
Visit our website and blog for more details.
Supporting quotes
Dor Shoef, Data Engineering Tech Lead, Resident Home
"At Resident Home, our e-commerce results are driven by real-time, accurate data. To achieve that, we moved to AuraDB with serverless graph analytics capabilities, given its combination of reliability, high availability, and powerful advanced algorithms. It was quick and easy: in less than a few hours, we were able to make the switch in our code and get it up and running. We could also scale up our graph analytics memory on-demand, for even faster results without touching the main instance's configurations."
Benjamin Squire, Principal Data Scientist, Audience Acuity
"Audience Acuity was founded to solve complex identity-resolution challenges. Our approach using Neo4j Graph Analytics for Snowflake ensures marketers stay ahead of the curve by stitching together records from 20 distinct data sources —encompassing 2.2 billion records— using SQL without ever moving the data. Neo4j's graph-powered algorithms provided advanced insights offering a transformative edge over traditional methods."
Devin Pratt, Research Director, Data Management, IDC
"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, Neo4j
"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."
*According to customer benchmark data, Neo4j Aura Graph Analytics provides 50-80% greater accuracy in DS/ML models over traditional non-graph analytics models, resulting in 2x improvement in overall efficacy of their insights.
Attributions and Disclaimers
Gartner, Gartner® Magic Quadrant™ for Cloud Database Management Systems, Henry Cook, Ramke Ramakrishnan, Xingyu Gu, Aaron Rosenbaum, Masud Miraz, December 18, 2024.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
About Neo4j
Neo4j, the Graph Database & Analytics leader, helps organizations find hidden patterns and relationships across billions of data connections deeply, easily, and quickly. Customers leverage the structure of their connected data to reveal new ways of solving their most pressing business problems, from fraud detection, customer 360, knowledge graphs, supply chain, personalization, IoT, network management, and more – even as their data grows. Neo4j's full graph stack delivers powerful native graph storage with native vector search capability, data science, advanced analytics, and visualization, with enterprise-grade security controls, scalable architecture, and ACID compliance. Neo4j's dynamic open-source community brings together over 250,000 developers, data scientists, and architects across hundreds of Fortune 500 companies, government agencies, and NGOs. Visit neo4j.com.
This News is brought to you by Qube Mark, your trusted source for the latest updates and insights in marketing technology. Stay tuned for more groundbreaking innovations in the world of technology.
