The execution of both transactional and analytical processes within a single database while automatically monitoring real-time data changes
Neo4j has introduced significant new features that empower customers, whether on the cloud or managing their infrastructure, to achieve up to a 100-fold acceleration in their analytical query speeds. Furthermore, it facilitates the execution of both transactional and analytical processes within a single database while automatically monitoring real-time data changes, ultimately leading to expedited mission-critical decision-making.
“Neo4j’s integration of operational and analytical workloads within a single database is now enhanced by the power of parallel runtime and change data capture, empowering our customers with real-time insights, cost-efficient data management, and simplified architecture,” said Sudhir Hasbe, Chief Product Officer, Neo4j.”
“Neo4j’s new capabilities enable modern law enforcement agencies to react with greater agility to mission-critical events, empowering them to fight more crimes and solve them faster”Anil Masakal, Engineering Leader, Dropbox
New capabilities and benefits include:
- Up to 100X faster performance of analytical queries via Parallel Runtime capability, which adds concurrent threads across multiple CPU cores to run analytical graph queries. Neo4j also leverages a technique called morsel-based parallelism to optimise this capability, for greater scalability, better resource utilisation, and seamless multitasking.
- Faster mission-critical decisions now enabled by native Change Data Capture (CDC), which automates the real-time tracking and notification of data changes in the database. CDC is also integrated with Neo4j Connector for Kafka and Confluent, which streams these changes for easier consumption across other data platforms and applications.
- Easier Knowledge Graph creation via new embedding models that predict and find missing relationships and infer new connections within an organisation’s knowledge graph for greater semantic understanding.
- New pathfinding algorithms thatmakecomplex workflows more efficient by identifying the best sequence and critical paths between nodes on a graph.
“Neo4j’s Change Data Capture capability enables us to synchronise the latest changes happening in our customers’ various data sources simultaneously – and helps us guarantee that when they use Dropbox Dash, they can search and find their content accurately,” said, Anil Masakal, Engineering Leader, Dropbox.