Anzo

Anzo by Cambridge Semantics is a knowledge graph platform designed to enable agile data integration, transformation, and analytics at enterprise scale. It is built for both small and large enterprises that deal with complex and diverse data sources and require scalable data integration and analytics solutions. Anzo is utilized by data scientists, analysts, IT professionals, data engineers, and business intelligence professionals across various industries, including financial services.

Key Features

Scalable Knowledge Graph Platform: According to the vendor, Anzo is built on a high-performance graph database engine called AnzoGraph, enabling agile data integration, transformation, and analytics at enterprise scale. It utilizes an in-memory MPP processing paradigm to execute queries quickly.

Data Onboarding and Integration: Anzo provides data onboarding pipelines, virtualization, and transformation capabilities, allowing for rapid cataloging and connection of structured and unstructured, internal and external data sources. Users can build highly integrated enterprise-scale knowledge graphs using flexible semantic graph models and AnzoGraph.

Semantic Definitions for Data Enrichment: Anzo adds a layer of semantic definitions on top of the graph, making the data easier to understand and use. Users can create, edit, or import models based on RDF and OWL using built-in modeling tools. Versioning and access control features are available for efficient model management.

Advanced Analytics Capabilities: AnzoGraph includes data science primitives, traditional OLAP analytics, graph algorithms, and geospatial functions. Users can apply these analytics natively within Anzo or connect with common data science and analytic platforms and tools.

Agile Data Supply Chain: According to the vendor, Anzo accelerates the delivery of new analytics-ready data products by providing an enterprise-scale knowledge graph of highly blended data for on-demand access. It allows for rapid generation of new combinations of datasets and exploration of pre-defined data products.

High-Performance In-Memory MPP Architecture: AnzoGraph's high-performance in-memory MPP architecture enables rapid data loading, modeling, and analysis at scale. It also supports Kubernetes, ensuring efficient resource utilization and scalability.

Flexible Semantic Graph Models: Anzo enables the creation of flexible semantic graph models, allowing users to define relationships and properties between data entities. This facilitates richer integration of data around intuitive business terms and definitions.

Seamless Integration with Data Science Ecosystems: Anzo supports Jupyter Notebooks, Apache Arrow Flight Protocol, HTTP/REST APIs, BI tools, and user-defined extensions (UDX), enabling seamless integration with new and existing data science and advanced analytics ecosystems.

Data Visualization and Exploration: Anzo's data visualization module allows for the exploration and analysis of knowledge graphs. It enables users to visually navigate and interact with the data, uncovering valuable insights.