Anzo

Additional features

Enterprise-Scale Knowledge Graph Toolset

A comprehensive set of tools for building and managing knowledge graphs at an organizational level.

Agile Data Integration

Enables quick and flexible integration of diverse data.

Agile Data Transformation

Facilitates rapid and adaptable data transformation processes.

Agile Data Analytics

Supports quick and flexible data analysis.

Semantic Layer

Adds real-world meaning to data, making insights clearer and connections explicit.

Eliminates Data Silos

Integrates disparate data sources to create a unified view.

Activates Unused Data

Makes previously unutilized data accessible for analysis.

Enables On-Demand Business Insight

Provides insights as needed by the business.

Provides Organizational Context

Knowledge graphs offer a comprehensive understanding of enterprise data for analytics and AI.

Supports Generative AI (GenAI)

Maps human thought and GenAI understanding to data storage and access for accurate answers.

Automates Scalable Graph Pipelines

Creates automated processes for managing graph data at scale.

Graph Lakehouse™

A high-performance Massively Parallel Processing (MPP) graph engine.

Fast Query Execution

Delivers results against large datasets in seconds.

Connect All Your Data

Data onboarding pipelines, virtualization, and transformation capabilities.

Rapidly Catalog Data

Quickly organizes and indexes data.

Rapidly Connect Data

Establishes connections between data sources efficiently.

Highly Integrated Enterprise-Scale Knowledge Graphs

Creates cohesive and extensive knowledge graphs.

Semantic Definitions Layer

Adds intuitive business terms and definitions on top of the graph for easier understanding.

Advanced Analytics

Supports discovering new insights using sophisticated analytical capabilities.

Hundreds of Data Science Primitives

Provides a wide range of basic data science functions.

Traditional Online Analytical Processing (OLAP) Analytics

Supports multi-dimensional data analysis.

Graph Algorithms

Includes algorithms specific to graph structures for network analysis, pathfinding, etc.

Geospatial Functions

Offers capabilities for analyzing geographic data.

Optimized for Analytics Speed and Scale

Designed for fast data loading and analytical queries.

Linear Scalability

Performance and data volume scale linearly as servers are added.

ACID Compliance

Supports Atomicity, Consistency, Isolation, and Durability for data transactions.

Transform Data in Graph at Scale

Unique ability to perform data transformation directly within the graph environment at scale.

Any Data at Any Scale

Handles structured and unstructured data from diverse sources.

Industry-Standard Languages

Supports Resource Description Framework (RDF) data model and labeled property graph model (W3C RDF* and SPARQL* proposed standard).

Inferencing and Semantic Analysis

Allows deriving new facts and understanding meaning from data relationships.

Build Customized Blended Data Products

Enables creation of tailored data sets from integrated sources.

Flexible Semantic Graph Modeling

Provides tools for building flexible semantic models.

MPP In-Memory Graph Engine

Utilizes in-memory processing for rapid data loading, modeling, and analysis.

Create, Edit, or Import Models

Built-in tools for managing semantic models.

RDF and Web Ontology Language (OWL) Support

Allows building models based on these standards.

Versioning and Access Control for Models

Manages development participation and changes to models.

Seamless Integration

Supports various external tools and ecosystems.

Jupyter Notebooks Support

Integrates with Jupyter for data science workflows.

Apache Arrow Flight Protocol Support

Enables high-performance data transfer.

HTTP/REST APIs Support

Provides interfaces for programmatic access.

BI Tools Integration

Connects with business intelligence tools.

User-Defined Extensions (UDX)

Allows for custom functionality development.