ArangoDB Enterprise: SatelliteGraphs
Graph database technology plays an important role in many large projects. Yet, in many cases it is not the graph that needs to be sharded but data stored as time series or JSON documents. Nonetheless, optimal performance is crucial for fast operational or analytical purposes and sometimes requires also the combination of data models.
ArangoDB SatelliteGraphs replicates one or more graphs to all machines within a cluster so queries can be executed locally. The replicated graph is orbiting the shards of a distributed collection on each DBserver. By combining sharding and replication in this way, each query engine on the DBservers can process queries locally and in parallel for optimal performance – avoiding network latency during query execution.
Figure 1: ArangoDB SatelliteGraphs Schema
SatelliteGraphs are designed to support the combination of data models and access patterns including graphs in distributed settings, and allows users to leverage the full power of multi-model for their projects.
Use Cases for SatelliteGraphs
Identity & Access Management, Network Management or analytics in IoT often involve large, sharded document or time series collections, but only contain small graphs for permission or analytical purposes. With SatelliteGraphs in ArangoDB, permission queries can be executed with sub-second latency, and analytical use cases can greatly benefit from local, parallel query execution. Leverage the whole computing power of your cluster when needed.
How SatelliteGraphs work
The coordinator layer knows where data needed for a certain query is located, and can push queries down to these servers. The query optimizer pushes down the query execution down to each query engine on the DBb servers for local query execution. Just the intermediate results get sent back to the coordinator. This greatly reduces network latency during query execution and allows for optimal usage of the available computing resources.
Getting Started with SatelliteGraphs
More Solutions for Graphs at Scale
Graphs are needed for various use cases and appear in very different shapes. ArangoDB provides optimized solutions for all shapes and sizes of your graph datasets and allows for high-end performance.
Disjoint SmartGraphs: Manage large scale hierarchical graphs and holistic graph analytics across customers
Enterprise Edition users can now work on complete new use cases or further optimize current graph-based applications. If you’d like to know more contact us about how you can further optimize your high performance clusters.