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Relavance Associative Database System

Relavance associative database system; the new standard for big data and analytics solutions


Relavance stores and retrieves information much like the human brain.  Our brain stores each atom of information networked to its associated concepts.  Your brain does not need to recall by writing a query, it instantly pulls up the associated information. So does our system.

The patent (link) is granted to us worldwide.


​10 reasons why Relavance

No data modeling

While ingesting different data streams the associative data model is automatically and atomically generated. No need for modeling data layers (more).

Extremely fast implementations

No need for data modeling, no need for internal data distribution to e.g. datamarts and automatic incremental loading, Savings are above 80% in time and therefore also in money. 

Just concentrate on requirements, clean data and discovery. 

Data agnostic

All data is stored atomically and connected to each other. The source is not relevant: if it is structured data or unstructured data, API, NoSQL, PDF or otherwise. Making it e.g. a full-text search engine

Lightening fast

The automatic creation of indexes on a field/concept level together with the patented technology causes all data to be connected in 4 reads in stead of a normal 30+ disk reads. 

Separation of data and data model

Because all data is stored atomically, the data model can be changed without moving data. Moreover, multiple data models can be used simultaneously. 

Data de-duplication

All data is de-duplicated. Resulting in approximately 70% less data.

Instant pattern and data discovery

Data can be ingested in minutes, discovery can be done immediately afterwards.


The storage of data is on disk because the disk is fast enough. Making a theoretically endless storage capacity possible.

Security by design

GDPR Proof and unhackable by the military because of three levels of 128-bit dynamic mathematical encryption. 

Automated machine learning

True augmented intelligence, integrated on a database level. This uses patterns to learn and not statistical models creating a traceable artificial intelligence.

This superb technology makes it useful for:

Database and Datawarehouse projects, IoT projects, AI projects, Blockchain projects/distributed ledger projects or ...

operational database projects

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