The Next Generation Graph Database
Anzo Graph Query Engine (AGQE), the most advanced in-memory graph analytic engine, is built to accommodate the wide variety of complex data that is characteristic of Big Data. AGQE enables users to execute rich analytics to uncover interesting connected patterns in their data.
Scale and Speed: Ask the Unknown Questions
The scale and speed of AGQE is tailored for big data’s two most immediate challenges. Its in-memory, parallel processing is central to the rapidity with which it parses through millions of semantic statements in seconds. Similarly, the scalable nature of AGQE’s distributed querying capabilities, instead of analyzing data linearly, enables it to process billions of triples in moments.
This relationship between scale and speed is complementary; AGQE’s speed allows it to process greater amounts of data in less time, accentuating the scalable semantic architecture of smart data lakes. The scale and speed of AGQE is an integral aspect of discovering insights never seen or asked before.
Standard Based: Built to be Flexible
Executing analytics with a wide variety and rapidly changing list of structured and unstructured data sources both from within the enterprise and externally required a graph database with greater insight. For this reason, AGQE was built around the standards-based W3C standard RDF/SPARQL and, as a result, AGQE strikes the right balance between ease-of-use, performance, flexibility and scale that is required by companies. These semantics standards are being further developed and adopted in industries like Financial Services with FIBO, Pharmaceutical with CDISC and Insurance with ACORD.
Enabling the Business to Ask Questions
AGQE is built for the business users to be able to see the connections between their data. This ability for a business analyst to collect all their data and see the patterns and associations on the fly is extremely valuable to the organization. No longer does the business need on to rely on and wait weeks or month for the IT Department to build and prepare the data for analyzing. The business user can now simply access their data, ask questions, formulate answers and then see even more data connections to ask forther questions never thought of before.