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Anzo Platform

The scaleable knowledge graph platform
for data integration and analytics.

Anzo makes turning siloed data into enterprise-scale knowledge graphs
faster and easier than ever. 
From there, anything’s possible.

Anzo Architecture

Generative AI Knowledge Graph Webinar

Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries against datasets extremely quickly, enabling agile data integration, transformation, and analytics at enterprise scale.  Anzo leverages standards including W3C’s RDF, OWL, SKOS, and SPARQL to combine knowledge graphs of metadata and data which can be powerfully explored, transformed and analyzed, while also ensuring open data interoperability and easy integration with other systems.  Anzo is an open overlay platform that allows users to assemble knowledge graphs against the underlying data resources without displacing or disrupting existing processes or platforms. Anzo integrates with enterprise metadata, governance, security controls and policies, and includes APIs for lights-out integration into other processes.

Connect All Your Data

Anzo’s data onboarding pipelines, virtualization, and transformation capabilities rapidly catalog and connect structured and unstructured, internal and external data sources into highly integrated enterprise-scale knowledge graphs. Users build customized blended data products using Anzo’s flexible semantic graph models and MPP in-memory graph engine, AnzoGraph. Rapid data loading, modeling, and analysis at scale are achieved through AnzoGraph’s high-performance in-memory MPP architecture and Kubernetes support.

Make Your Data Easier to Use with Semantics

Anzo adds a layer of semantic definitions on top of your graph, allowing for richer integration of the data around intuitive business terms and definitions, making the data easier to understand and use by more people. Built-in modeling tools let users create, edit, or import models based on RDF and OWL, while versioning and access control allow users to manage and control which users participate in model development.

Discover New Insights Using Advanced Analytics

AnzoGraph includes hundreds of data science primitives, traditional OLAP analytics, graph algorithms, and geospatial functions to support a wide variety of analytic use cases. Users apply these natively within Anzo or connect with common data science and analytic platforms and tools. Support for Jupyter Notebooks, Apache Arrow Flight Protocol, HTTP/REST APIs, BI tools, and user-defined-extensions (UDX) allow Anzo to seamlessly integrate with new and existing data science and advanced analytics ecosystems.

Accelerate Data Delivery with a Modern Agile Data Supply Chain

Anzo accelerates the delivery of new analytics-ready data products by providing the organization with an enterprise-scale knowledge graph of highly blended data for on-demand access. AnzoGraph’s high performance in-memory data transformation and blending tools and data visualization module allow for rapid generation of new combinations of datasets, as well as exploration of pre-defined data products. IT teams deploy custom search, analytic or operational applications directly against the knowledge graph while business users connect BI and analytics tools to the knowledge graph for rapid data access. Anzo’s knowledge graph replaces redundant data provisioning requests and pipelines, to reduce IT overhead, and improve the security, efficiency, and compliance of the data supply chain.

Developers: Embed AnzoGraph in Your Application! - Learn more

Optimized for analytics speed and scale

Ultra-fast data loading and analytical queries. Performance and data volume linearly scales as you add servers. Supports ACID. Unique in its ability to transform data in graph to scale.

Any data at any scale with industry-standard languages

Handle structured and unstructured data from diverse data sources. Supports both the standard RDF data model and labeled property graph model (using W3C RDF* and SPARQL* proposed standard). OpenCypher support is coming soon.

Apply Analytics to Connected Data At Scale

Analyze data in graph format using inferencing and semantic analysis, graph algorithms, data warehouse-style OLAP analytics, data science functions, and geospatial functions.

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