Sparksee · graph database management system

The graph engine that ships inside your product

High-performance, compact, embeddable. Sparksee represents and analyses complex interrelationships between entities, with the security and integrity guarantees enterprise data demands.

A graph of connected communitiesAn illustrative graph. Several colour-coded communities each fan out from a densely connected hub, and the hubs are linked to one another so the whole graph stays connected.

Why Sparksee

Six reasons teams choose an embedded graph store over a clustered one.

Connectivity resilience

Once you have the graph in your mobile device, your analytics do not depend on the cloud.

Increased privacy

Enables the creation of privacy preserving apps, where data is stored in the user's device.

Reduced memory usage

Sparksee has a compact data representation and management that reduces the amount of required resources.

Advanced algorithms

Our built-in algorithms accelerate the creation of applications with out-of-the-box tooling.

Recovery

Sparksee technology is data resilient, so that you don't have to worry about crashes.

Reduced latency

Our graph database is fast at computing on your mobile device, and you do not need to wait for a server's response.

Why companies embed Sparksee

Sparksee stores graphs as compact bitmaps, so graph algorithms run fast even on mobile and embedded hardware.

It works out of core and persists data to disk, with disk-level encryption that keeps data private if a device is lost, stolen or sold, and recovery when a database file is corrupted.

Graph computation on the device

A graph database on the device keeps the service running when connectivity is poor or absent, and answers faster when the network is saturated. Moving computation from the cloud to the device can also cut a provider’s cloud costs significantly.

Our patented bitmap representation

A way of representing graphs that makes the most of each level of the memory hierarchy:

  • The graph is split into smaller structures so the parts that matter stay in cache
  • Compact object identifiers (OIDs) reduce memory requirements
  • Dedicated structures speed up navigating and traversing edges
  • Every attribute is indexed, so queries can filter on any of them
View patent US8312052B2
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