AnzoGraph Features and Benefits
AnzoGraph is a native, massively parallel processing (MPP) graph OLAP database, built to deliver hyperfast advanced analytics at big data scale. This topic provides details about the key AnzoGraph features and the benefits that they provide.
- Native Graph Database
- Massively Parallel Processing
- Performance at Scale
- Graph OLAP Technology
- Standards-Based Query Languages and Protocols
- Advanced Analytics
- Flexible and Schema-less Data Loading
- Multi-Graph Support
- Sample Files, Tutorials, Notebooks, and Benchmarks
AnzoGraph is built to handle graph workloads throughout the computing stack, from the query language to the database and memory management engine, and the file system. Data is stored in native graph format whether it is on disk or in memory. AnzoGraph's use of the organic graph model avoids the overhead that non-native graph databases employ for simulating graph traversal and reformatting data on disk. AnzoGraph processes queries faster, scales better, and runs efficiently on hardware, virtual, or cloud platforms.
AnzoGraph is a massively parallel processing (MPP) graph database. Its compressed in-memory and on disk data storage and MPP design provides extremely fast data loading, real-time updates, and interactive analytics on huge amounts of data. For more information, see AnzoGraph Architecture.
AnzoGraph scales with your needs by distributing graph data across cluster nodes and processing queries in parallel on all nodes. Because of AnzoGraph's MPP and fast intra-cluster network implementation, load and query performance increases as the data and cluster size grow.
Unlike transaction-oriented graph databases, AnzoGraph is a modern enterprise Graph Online Analytics Processing (GOLAP) database that enables users to interactively view, analyze, and update graph data. AnzoGraph provides unmatched analytic processing of complex queries that require many joins, filters, and aggregation. AnzoGraph enables data scientists, data architects, and application developers to deliver supercharged analytic insights at massive scale to support vital real-time solutions for detecting fraud, ensuring compliance, optimizing supply chains, building enterprise knowledge bases, and more.
AnzoGraph adheres to the W3C RDF and SPARQL 1.1 standards and offers the standard SPARQL 1.1 and RDF Graph Store Protocol on HTTP/S for sending and receiving SPARQL queries between client applications and the database. AnzoGraph also supports the industry standard CSV and RDF load file formats. Developers and analysts do not need to learn a proprietary query language to work with AnzoGraph and can incorporate AnzoGraph into their existing infrastructure of products that support standard graph APIs, such as data preparation, graph transaction processing, visualization, business intelligence, and machine learning tools.
In addition to SPARQL, AnzoGraph also provides Cypher query language support, allowing you to query AnzoGraph graph databases and data sets, taking advantage of AnzoGraph's high performance query execution and scalability. AnzoGraph supports the Bolt protocol to provide a Cypher-based CLI from which users can directly execute Cypher statements. Other Cypher applications that use the Bolt protocol can also execute either Cypher or SPARQL queries and other commands against AnzoGraph data. For more information on AnzoGraph Cypher language support, see Working with Cypher and the Movies Graph Database and the Cypher Language Reference (Preview).
AnzoGraph extends the SPARQL 1.1 specification to add support for advanced analytics such as window aggregates and advanced grouping capabilities. AnzoGraph also supports conditional expressions, named queries and views, inferencing (RDFS+), labeled property graphs (using the W3C RDF* proposed standard), and graph algorithms. AnzoGraph provides two packages of pre-built data science and geospatial extension functions that you can also use in the same way as other native, built-in analytic functions. These functions provide additional statistical and location or geographical analytic capabilities, respectively. For more information about using built-in analytic capabilities as well as the additional function extensions, see Using Standard SPARQL Commands and Functions.
In addition to supporting all standard SPARQL functions, AnzoGraph includes a rich library of SQL and Microsoft Excel-like built-in functions as well as both C++ and Java APIs for creating user-defined or custom extension functions, aggregates, and services. For more information about the extensions, see Developing AnzoGraph Extensions.
Loading data to AnzoGraph does not require maintenance of error-prone and time-consuming ETL pipelines, rigid schemas, or relational database models. And AnzoGraph’s virtually unlimited capacity and real-time performance enables users to load structured, unstructured, internal, or external data on-demand, bringing immediate access and analysis to everyone. For more information about loading and accessing data, see Connecting to Data Sources and Managing Data as well as Accessing and Visualizing Data in AnzoGraph.
In accordance with the RDF/SPARQL standard, AnzoGraph has robust multi-graph support with SPARQL and AnzoGraph adds multi-graph support to Cypher with its support of that language.
AnzoGraph provides a number of different data samples, tutorials, and notebooks to help you get started quickly using AnzoGraph and also familiarize you with the various operations you can perform: loading data and running SPARQL and Cypher queries. In addition, a number of benchmark scripts are provided to measure performance by running a variety of queries against data at scale in your environment. For more information, see Accessing and Visualizing Data in AnzoGraph as well as Sample Data, Tutorials, and Benchmarks.