Neo4j Brings Graph Analytics to Any Data Platform

Graph database and analytics firm Neo4j has announced the launch of Neo4j Aura Graph Analytics, a new serverless offering that it says can be used seamlessly with any data source.

Neo4j says its offering makes graph analytics capabilities accessible to everyone and eliminates adoption barriers by removing the need for custom queries, ETL pipelines, or specialized graph expertise. This allows business decision-makers, data scientists, and other users to focus on outcomes.

Neo4j Aura Graph Analytics

Deployed as a fully managed, serverless cloud service, Neo4j Aura Graph Analytics requires no infrastructure setup and no prior experience with graph technology or the Cypher query language.

Users can seamlessly deploy and scale graph analytics workloads end-to-end, enabling them to collect, organize, analyze, and visualize data. It also comes with over 65 ready-to-use graph algorithms and is optimized for high-performance applications and parallel workflows.

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, as well as all cloud data warehouses and data lake platforms, including Databricks, Snowflake, Google BigQuery, and Microsoft OneLake.

Graph databases excel at queries involving relationships, such as finding the shortest path or friends-of-friends. They also offer constant-time traversal, and query performance doesn’t degrade much even as data size grows.

Because they don’t require a fixed structure, graph databases are ideal for agile development or areas where the data keeps changing. Unsurprisingly, graph database use has been growing rapidly.

“Our vision with Aura Graph Analytics is simple: make it easy for any user to make better business decisions faster,” said Sudhir Hasbe, the chief product officer at Neo4j. “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.”

Neo4j Aura Graph Analytics is available for all data sources through Pandas dataframes in Python. Support for all other major languages is expected later this year.

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