Graph databases gain in popularity due to relationship insight capabilities
With the growing importance of data that tells a story and delivers business insights to companies, it’s not surprising that demand for graph databases is on the rise.
These databases use graph structures for semantic queries with nodes, edges and properties to represent and store data. Graph databases make the relationships between data elements a priority, and querying relationships within a graph database is fast because they are perpetually stored within the database itself. The relationships can be intuitively visualized using graph databases.
The technology provides advantages for overcoming problems companies face when analyzing large and complex data as compared with other database systems, according to market research and advisory firm Allied Market Research. For example, there’s the ability to scale and handle naturally large data sets.
Allied valued the global graph database market size at $651 million in 2018, and projects it to reach $3.73 billion by 2026, growing at a compound annual growth rate (CAGR) of 25% from 2019 to 2026.
Among the market drivers is the massive growth in data volumes. Managing data using a traditional relational database infrastructure is difficult for enterprises, the report said. Also contributing to rising demand is the need for better response times and accuracy in discovering new data correlations.