Second, the underlying structure is not optimized for graph operations. We don’t describe TigerGraph as an in-memory database, because having data in memory is a preference but not a requirement.

Memgraph is the creator of an in-memory graph database that can be used by developers to create so-called graph applications. They leverage real-time data streamed from multiple sources such as ...

Graph databases like this shouldn’t be confused ... Two versions are available, with different memory options built on reserved capacity so you don’t need to worry about instances not being ...

By deploying a highly distributed, massively parallel query engine based on in-memory processing of semantic data in smart graph databases, organizations can analyze whole data sets incorporating an ...

TigerGraph chose Neo4j because it's a native graph database and a market leader ... Hadoop's MapReduce parallelism for processing and in-memory, disk and compression techniques for storage.

Graph databases are increasingly using the Non-Volatile Memory Express (NVMe) standard for Solid State Drives (SSDs) to increase application performance and significantly reduce recovery elapsed ...

NASA's people analytics group has swapped its Neo4j graph database for Memgraph due to costs.… David Meza, senior data scientist on the team, told a recent webinar that despite using Neo4j for ...

The fast-rising pace of attacks is driving a graph database arms race across leading cybersecurity providers. Microsoft‘s Security Exposure Management Platform (MSEM) at Ignite 2024 reflects how ...