The Knowledge Liquidity Platform's (KLP) patent pending technology allows you to create high-capability big data architectures very quickly.
KLP consists of an end-to-end ecosystem of products for capabilities from ingestion, persistence, integration, analysis, governance, to data science.
KLP products can be used to create new high performance enterprises, or to supplement existing systems.
KLP products conform to open standards wherever possible to prevent vendor lock-in and improve integration.
Most KLP products can be used in standalone mode.
Datanova also offers turnkey solutions for specific domains such as social media analytics, banking, insurance, and healthcare.
These consist of KLP configured and fine-tuned for specific use cases.
A full list of products is provided here. Some of the main functional products are:
HELIOS big data management system is the persistence module of KLP. It can deploy various kinds of data (XML, relational, text, binary, etc.) in governed, indexable, secure, and queryable NoSQL.
Helios can federate to existing databases to provide a seamless federation.
APOLLO universal translator is the KLP semantic data integration module. It provides the most expressive data integration in the market today.
Apollo can be deployed in various settings such as cloud scale ETL or on-demand (query time) integration.
VULCAN analytics framework provides a rubric to deploy, combine, manage, and monitor analytics.
It comes pre-loaded with analytics for various domains, but it is much more. It provides advanced tools to create analytic life cycles, and ties them to data life cycles.
Thus Vulcan improves return on analytic investment.
DELPHI architecture management provides full data lineage and manages the various aspects of a hybrid (i.e. cloud and non-cloud) data architecture.
Delphi provides unique capabilities such as live query on the data architecture for current reports, and living architecture (i.e., the data is corrected when the architecture changes)
DSO (Data Science Office) is a web enabled data science environment. It provisions all KLP products in a fluid environment where they can be combined with each other.
DSO provides the latest data science tools such as SQL, SPARQL, and Python along with all of KLP to make an ultra-powerful tool for the data enthusiast.
All KLP products and data architecture are configured using a 4th generation language (4GL) called K4.
This language is built specifically for semantics and big data.
Everything from ingestion, security, schemas, triggers, to queries can be controlled in this powerful language.
K4 can describe the full data architectue of the system as well as its intended operation.
Architectures described by K4 are automatically implemented in the KLP baseline.
K4 links to open standards such as XSD and OWL, providing seamless operation with other data systems and reducing vendor lock-in.
K4 is a major contributor to the low implementation and operational costs of KLP systems.
- Red Hat Enterprise Linux 5 (x64)
- Red Hat Enterprise Linux 6 (x64)
- CentOS 5 (x64)
- Microsoft Windows Server 2008 (RDBMS
- Microsoft Windows 7, 8, 8.1 64-bit (RDBMS
- Microsoft Azure
- Amazon EC2
- VMware ESX (private cloud deployments)