Time dimension is fundamental in many different contexts, from statistical analysis to representation of cause-effect relationships, from forecasting to automatic control systems.
Representing this kind of data in "traditional" databases can lead to performance problems, due to their quantity, frequency and domain model; this is why NoSQL solutions are widely used in this field.
In this talk we will show how to use OrientDB, a Document-Graph Database, to store, process and query this type of information in an efficient and effective way.
Time dimension is fundamental in many different contexts, from statistical analysis to representation of cause-effect relationships, from forecasting to automatic control systems.
Representing this kind of data in "traditional" databases can lead to performance problems, due to their quantity, frequency and domain model; this is why NoSQL solutions are widely used in this field.
In this talk we will show how to use OrientDB, a Document-Graph Database, to store, process and query this type of information in an efficient and effective way.