A new generation of graph databases has taken hold, and a generation of query languages has arrived alongside them. The assorted graph database query languages include the likes of Gremlin, Cypher ...

For example, TigerGraph recently used these benchmarks to scale its database to support 30 terabytes (TB) of graph data, up from 1 TB in 2019 and 5 TB in 2020.

Based on this schema, we defined queries that populate data into the graph and queries that retrieve data from the graph. Let’s look at a graph query that generates recommendations.

The gist of what's going on is that we have a war for graph database domination, and query language is a key battle to be won. SQL did not arrive at universal adoption overnight. If there is a ...

The global graph database market size to grow from USD 2.9 billion in 2023 to USD 7.3 billion by 2028, at a Compound Annual Growth Rate (CAGR) of 20.2% during the forecast period.

Abstract: Graph data, e.g., social and biological networks, financial transactions, knowledge graphs, and transportation systems are pervasive in the natural world, where nodes are entities with ...

The Graph is a decentralized protocol for indexing and querying blockchain data. But it's more than just a protocol: The Graph also has an implementation, which is open source and uses GraphQL.

The Multi-Query Optimization (MQO) problem is a class of data-intensive problems that are NP-hard, and it has applications in many fields such as database query optimization, machine learning ...