When to use DSE Graph
A description of the environments when DSE Graph is the optimal choice for storing data.
Built on Apache Cassandra®, DataStax Enterprise (DSE) adds operational reliability hardened by the Fortune 100 and supports more workloads from graph to search to analytics. Easily deploy the only active-everywhere database platform that runs wherever needed: on-premises, across regions or clouds.
Each commercial extension, such as DSE Graph, inherits the benefits of Apache Cassandra as part of DataStax Enterprise's database while adding the ability to adapt to enterprise needs with other models such as graph or JSON data storage.
- Comprehensive data model
- Data is database centric with single query
- Entities and relationships are queried
- Application is read heavy
- Heavy denormalization
- Data is application centric with multiple queries
- Individual entities are queried
- Application is write heavy
DSE Graph is an extension of the DSE database that reaps benefits if the data is highly connected. The graph data model is simple to understand. The connectedness of the data reveals both depth and breadth to the relationships between entities. DSE Graph uses query optimization that automatically parallelizes as much of the query as possible to increase performance. Graph index structures are used to create optimal entry points for queries before starting a graph traversal. Graph partitioning handles vertices with extreme connectedness to prevent hotspots during graph traversal. All of these aspects of DSE Graph take advantage of the underlying DSE database that is used to store DSE Graph data.