When it comes to getting value from data, there is nothing more important than speed and quality. Quality delivers accuracy and speed delivers relevance. RedPoint Global, a leading provider of data management and customer engagement technology, announced findings from a new benchmark study conducted by information management leader MCG Global Services, which revealed leading performance from RedPoint Global’s Data Management™ application. The benchmark study not only established that RedPoint’s inherent distributed processing design significantly outperforms competing approaches, it also, according to the study’s authors, was far simpler to implement and operate.
Findings showed that RedPoint Data Management (DM) exceeded previous benchmarks and client engagements in usability, maturity, data quality, and speed – completing the same workload 550 percent faster than Spark and 1,900 percent faster than a MapReduce-based Tez/Hive approach. Real-life scenarios were used to showcase how important the underlying YARN-based architecture is in exploiting the vast computational power of Hadoop. Organizations looking for the highest levels of compute performance, data quality and ease of use will appreciate the cost effectiveness, scalability and overall lower total cost of ownership of RedPoint over other data management platforms for Hadoop.
The RedPoint Data Management benchmark results were beyond what we thought possible – not only did RedPoint surpass previous benchmarks in several key areas, but the installation and setup of RedPoint Data Management Site and Execution Servers and Client tool also took less than 1.5 hours,” commended William McKnight, President of MCG Global Services and co-author of the independent survey. “RedPoint’s architecture foundation and finely tuned platform utilizing YARN offer a winning combination for success.”
These results stem from RedPoint’s ability to leverage the Hadoop cluster for distributed processing via YARN with minimal overhead. As one of the first certified on Hadoop 2.0, which introduced YARN, RedPoint’s platform was designed as a parallel processing architecture. Starting with a high-performance, data quality system, RedPoint does not require ‘interpreters’ like MapReduce or Spark to manage files in Hadoop but does so by using its native engine and most uniquely does not generate any code that must then be interpreted. This test proved that RedPoint users could not only load and organize data in Hadoop faster than other solutions, but do so without needing additional technologies available in the Hadoop ecosystem. RedPoint is also known for delivering its robust technology in the cloud, on-premise and via hybrid deployments, offering users easy access to flexible compute power.
RedPoint Data Management delivers an incomparable level of agility and performance more than 15 to 20 times faster than our previous tools,” said Steve Rao, CEO, Farm Market iD. “This is particularly important as we are quickly approaching one quadrillion data points. So obviously a robust yet flexible solution like RedPoint’s is critical for us. The platform has helped us manage complex, high volumes of data with incredible precision all under one application umbrella, allowing us to develop and deliver customized insights in record time without needing another product, programming or specialized experience.”
Key Findings of the Study and Use Case Results Include:
Web Log Data Analyzed Against Product Orders Use Case
- RedPoint was able to complete the same workload correlating products ordered with page views and coupon campaign click-throughs on an e-commerce website 550 percent faster than using Spark and 1,900 percent faster than using a MapReduce-based Tez/Hive approach.
Usability: Efficiency, Effectiveness, and Satisfaction
- Installation and setup of RedPoint DM in Hadoop took less than 1.5 person-hours. Configuration of the Hadoop tools for use with RedPoint DM took less than 0.5 person-hours.
- RedPoint DM User Interface Satisfaction was rated “Very Easy.” According to the benchmark authors, “In our experience, most other vendor tools rate from easy to moderately difficult.”
Address Standardization and Name Matching Use Case
- RedPoint’s Address Standardization workload processed 10 million records on a three node Hadoop cluster, which will scale proportionately on larger clusters, at a rate of 66,667 records per second.
- RedPoint’s Name Matching was achieved at 58,140 records per second on a three node Hadoop cluster, which will scale proportionately on larger clusters.
- Typically, these types of data quality activities can take significantly longer using traditional approaches and technologies.
This benchmark proves something our customers have known all along – that RedPoint is the gold standard for Big Data Management,” said Dale Renner, CEO and founder of RedPoint Global. “RedPoint Data Management is architected specifically for organizations that want to get the most value from their data and need to make decisions at the ever accelerating speed of business. Our unique approach to data management in Hadoop offers supreme performance you simply won’t find anywhere else.”
The study, which measured fundamental business problems that typical organizations might encounter, leveraged data management scenarios, including integrating data from transactional systems; solving data ingestion problems related to relational data, web-click logs, coupon logs; and measuring performance of name matching and address standardization.
Earlier this year, for the second time in a row, RedPoint received the highest score in both the Data Integration and Operational/Transactional Data Quality Use Case categories in Gartner’s Critical Capabilities for Data Quality Tools Report [1]. RedPoint also received the second highest scores in Data Migration, Big Data & Analytics and Master Data Management; and the third highest score in Information Governance Initiatives.
[1] Gartner, Critical Capabilities for Data Quality Tools, Ted Friedman, Saul Judah, 18 December 2015
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This latest MCG Global Services benchmark is a step in the right direction. But there’s still more that can be done. Our CEO recently challenged Talend and Informatica to a three-way benchmark test to see whose approach to data management really is the best. Unfortunately, we haven’t heard a response from either company yet. http://blog.redpoint.net/talend-informatica-lets-get-real/