Cambridge Semantics, the graph-based provider of analytics and data management services, claimed a benchmark record this week for database query performance running on a public cloud platform.
The Boston-based analytics vendor said Wednesday (Dec. 7) its Anzo Graph Query Engine completed a load and query of 1 trillion “triples” on the Google Cloud Platform in just less than two hours. That result, the company claimed, was 100 times faster than other query engines running on a metric called the Lehigh University Benchmark operating at the same data scale.
The company said examples of 1 trillion triples include six months worth of global Google (NASDAQ: GOOGL) searches or 100 million facts describing the details of 10,000 clinical trial studies—in other words, a lot of data.
Barry Zane, vice president of engineering at Cambridge Analytics, noted that a major challenge for semantic-based analytics “has been enabling a load and query performance on very large data sets from a data lake” that are being demanded by enterprise analytics users. Zane claimed the benchmark test validated that the loading and querying steps, a process that previously took businesses more than a month, could now be performed in less than two hours.
Cambridge Semantics also is touting the benchmark results to promote its graph-based online analytical processing approach as data diversity and volumes grow. The company further argues that current relational database management systems are failing to keep pace with soaring data volumes and the onslaught of unstructured data and streaming video from social media, Internet of Things and other sources.
The Anzo Graph Query Engine is a clustered, in-memory graph analytics engine based on open semantic standards that intended for ad hoc and interactive queries and analytics across large and varied data sets. The query engine runs on dedicated servers or, in the case of the benchmark test, can be provisioned on cloud infrastructure such as Google Cloud Platform.
The Lehigh benchmark is designed to evaluate the performance of semantic web repositories based on queries of large datasets.
Earlier this year, Cambridge Semantics acquired the intellectual assets of graph database specialist SPARQL City, which was co-founded Zane. At the time, the company said the addition of SPARQL City’s in-memory graph query engine would expand its Anzo query engine based on semantic web technology. The platform is intended to help customers develop interactive, real-time data analytics capabilities.
Recent items:
Cambridge Semantics Buys Graph Database Specialist
A Semantic Approach to Big Data Governance
April 26, 2024
- Satori and Collibra Accelerate AI Readiness Through Unified Data Management
- Argonne’s New AI Application Reduces Data Processing Time by 100x in X-ray Studies
April 25, 2024
- Salesforce Unveils Zero Copy Partner Network, Offering New Open Data Lake Access via Apache Iceberg
- Dataiku Enables Generative AI-Powered Chat Across the Enterprise
- IBM Transforms the Storage Ownership Experience with IBM Storage Assurance
- Cleanlab Launches New Solution to Detect AI Hallucinations in Language Models
- University of Maryland’s Smith School Launches New Center for AI in Business
- SAS Advances Public Health Research with New Analytics Tools on NIH Researcher Workbench
- NVIDIA to Acquire GPU Orchestration Software Provider Run:ai
April 24, 2024
- AtScale Introduces Developer Community Edition for Semantic Modeling
- Domopalooza 2024 Sets a High Bar for AI in Business Intelligence and Analytics
- BigID Highlights Crucial Security Measures for Generative AI in Latest Industry Report
- Moveworks Showcases the Power of Its Next-Gen Copilot at Moveworks.global 2024
- AtScale Announces Next-Gen Product Innovations to Foster Data-Driven Industry-Wide Collaboration
- New Snorkel Flow Release Empowers Enterprises to Harness Their Data for Custom AI Solutions
- Snowflake Launches Arctic: The Most Open, Enterprise-Grade Large Language Model
- Lenovo Advances Hybrid AI Innovation to Meet the Demands of the Most Compute Intensive Workloads
- NEC Expands AI Offerings with Advanced LLMs for Faster Response Times
- Cribl Wins Fair Use Case in Splunk Lawsuit, Ensuring Continued Interoperability
- Rambus Advances AI 2.0 with GDDR7 Memory Controller IP
Most Read Features
Sorry. No data so far.
Most Read News In Brief
Sorry. No data so far.
Most Read This Just In
Sorry. No data so far.
Sponsored Partner Content
-
Get your Data AI Ready – Celebrate One Year of Deep Dish Data Virtual Series!
-
Supercharge Your Data Lake with Spark 3.3
-
Learn How to Build a Custom Chatbot Using a RAG Workflow in Minutes [Hands-on Demo]
-
Overcome ETL Bottlenecks with Metadata-driven Integration for the AI Era [Free Guide]
-
Gartner® Hype Cycle™ for Analytics and Business Intelligence 2023
-
The Art of Mastering Data Quality for AI and Analytics
Sponsored Whitepapers
Contributors
Featured Events
-
AI & Big Data Expo North America 2024
June 5 - June 6Santa Clara CA United States -
CDAO Canada Public Sector 2024
June 18 - June 19 -
AI Hardware & Edge AI Summit Europe
June 18 - June 19London United Kingdom -
AI Hardware & Edge AI Summit 2024
September 10 - September 12San Jose CA United States -
CDAO Government 2024
September 18 - September 19Washington DC United States