Data Storage

AggreGate Server stores enormous amount of data collected from a device network and generated internally:

Definitions and configuration of server modules and system resources History of synthetic internal metrics and events
Models of business objects and their relations Persistent events received from the network
Historical values of device metrics Audit trail of all system operations and events

All types of data stored by the server are divided into just a few major groups: configuration, events, binary blocks, statistics, and topologies. This simple division provides absolute flexibility in adding new types of devices and business objects without changing the structure of data storage.

Each of the above data items may be stored in several types of data storage facilities:

Relational Databases

Relational Databases

Offering a standard approach and failover clustering capabilities, this storage option has limited event insertion performance substantiated by limitations of any SQL database.

Key-Value Databases

Key-Value Databases

This integrated storage type is ideal for combining the extremely high configuration items update rate with failover clustering functionality.

NoSQL Databases

NoSQL Databases

Integrated NoSQL database engine offers very high insertion rates and failover clustering, as well as storage-level horizontal scalability by employing multi-server storage.

Graph Databases

Graph Databases

Graph storage facility houses large-scale topological structures. These can be network topologies, hierarchies of services, configuration management databases, electrical and piping schemes, and more.

Round-Robin Databases

Round-Robin Databases

Round-robin database is a time series storage facility that keeps numeric values aggregated by time periods. It offers constant disk/memory footprint and extremely fast storage/acquisition rates.

File-Based Storage

File-Based Storage

Plain file storage type is normally used by embedded server installations on systems with limited resources. Its operation minimizes CPU power and memory consumption.

Storage Matrix

Each storage facility has its pros and cons. It is also compatible with a specific set of data item types: