Graph Database
A graph database is a database that uses graph structures for semantic queries with nodes, edges and properties to represent and store data.
WHAT IS Graph Database ?
We live in an era of big data. During the last decade, from the advent of smartphones to advent of IoT, modern society is developed by many users and devices which have constantly consumed and produced a large volume of data. And we called it ‘Big Data’ or ‘Data Explosion’. As data is getting bigger and more connected, the importance of data management has been increasing by day. This massive volume of data is stored and analyzed for major business decisions. So, how do your company find and manage business value of accumulated big data? Identify the actionable business values with graph database.
Graph data model is very promising because of their Simplicity and Intuitiveness.
AgensGraph provides business Insight with optimized big data solutions.
Graph database is a collection of nodes and edges(relationships). A node represents an entity and an edge represents a relationship between the two nodes. Graph database focuses on the relationship between data. It is essential for managing connected data which deals with the relationships between data.
What is Node?
A unit to express one object within a domain such as a row of RDBMS table or document of Document DB.
What is Edge (Relationship)?
A unit to express the relationship between objects within a domain such as Foreign Key of RDBMS table or linked id of Document DB.
With more than 30 billion IoT devices expected to be in service by 2020(*Gartner), Big data from connected IoT devices has become an urgent concern. Graph DBMS provides fast performance for processing big data by querying the nodes and related edges(relationships) only.
The Benefits of Graph Database
Time to Market
Developing with graph database allows you to accelerate time-to-market where business decision to actualization is critical. Graph database should be considered a priority for “agile” teams.
Solid Performance
Graph database performance does not degrade as the number of data relationships increase contrary to that of conventional relational database. Traversing data using graph database is smartly designed so that it can minimize the execution time while relational database takes more time by scanning all the joined table records.
Flexibility
Graph database allows you to reform your data with super flexibility as your organization’s needs and environments change. It requires much less effort to integrate hetero data because graph database expands data using nodes and edges. Often described as schema-less, different types of schema can be implemented.