those that claim multi-model semantics where one system can purportedly support several data models. There is a considerable difference between the architecture of native graph storage and querying, ...

It isn’t clear yet how Microsoft’s all-in-one architecture measures up to native graph databases in terms of performance, but Cosmos DB certainly offers a useful combination of flexibility and ...

Graph databases excel for apps that explore many-to-many relationships, such as recommendation systems. Let’s look at an example Jeff Carpenter is a technical evangelist at DataStax. There has ...

work side-by-side with a graph processing engine (GPE) to handle of data and algorithms and by using parallelism and a distributed architecture. TigerGraph treats the graph as both a storage and a ...

to specify the corresponding shapes graph used to describe the link between a given shape and targeted data. Franz claims its upgraded, flexible architecture makes it the first graph database vendor ...

Aerospike Inc., maker of a highly scalable NoSQL database, today is entering ... Aerospike said the underlying architecture of its new graph offering permits it to surpass its competitors in ...

Graph database startup TigerGraph Inc. today announced ... doing this is difficult because their architecture doesn’t allow such connections to be discovered easily, making analytics a time ...

parallel shared-nothing architecture.” This delivers a greater degree of scalability than can be achieved by other mechanisms, Yu says. For example, Microsoft is using the TigerGraph database to power ...

Signals are converging and leading me to believe that 2025 is the Year of the Knowledge Graph. But before we get carried away ...

massively parallel graph database architecture, already the industry's performance leader as certified by LDBC. Optimized performance and management of OLTP and OLAP traffic through dedicated ...

Whether IT leaders opt for the precision of a Knowledge Graph or the efficiency ... RAG and how complex their data is, then compare their needs with each data architecture’s pros and cons.