Deep Engine Brings Enterprise-Level Performance to MySQL Databases

 
 
By Frank Ohlhorst  |  Posted 2015-04-24
 
 
 
 
 
 
 
 
 
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    Deep Engine Brings Enterprise-Level Performance to MySQL Databases
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    Deep Engine Brings Enterprise-Level Performance to MySQL Databases

    By Frank Ohlhorst
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    Deep Engine Operates at the Kernel Level
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    Deep Engine Operates at the Kernel Level

    Deep Engine is much more than a simple storage engine. The technology interacts at the kernel level of the database to empower its algorithms to use machine learning techniques, thus creating an environment that is adaptive and predictive for record retrieval.
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    Deep Engine Delivers Significant Performance Gains
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    Deep Engine Delivers Significant Performance Gains

    Indexed Insertion Benchmark (iiBench) testing shows that pedestrian database functions, such as row insertion and reindexing, experience a 64-fold increase in performance when compared with innoDB, the native storage engine for MySQL.
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    It Also Improve  Data Ingestion Tasks
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    It Also Improve Data Ingestion Tasks

    Deep Engine brings performance improvements to standardized tasks, such as data ingestion, which is a common occurrence for building big data sets. Deep's integrated heuristics and machine learning capabilities, along with support for multiple threads, increase parallel data importation by more than 20 times.
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    Deep Engine Speeds Up MySQL Query Results
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    Deep Engine Speeds Up MySQL Query Results

    Deep Engine brings as much as a twofold performance increase to MySQL queries. Several technologies combine to make that possible, including multiple threads, faster decompression and predictive integrated analytics, which over time learn the shortest path to the data.
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    Deep Engine Improves Compression, Decompression Performance
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    Deep Engine Improves Compression, Decompression Performance

    Deep Engine increases compression/decompression events by leveraging a multi-threaded kernel, as well as new compression algorithms that can increase both the level of compression and the speed at which compression and decompression events occur.
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    Transaction-Based Reads and Writes
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    Transaction-Based Reads and Writes

    In the real world, database performance ultimately comes down to transaction processing speed. Here, Deep Engine's use of machine learning heuristics brings self-tuning capabilities to MySQL, which when combined with improved compression and multiple threads along with advanced caching can bring significant transactional performance improvements to very large MySQL databases.
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    Meeting the Demands of IoT Analytics
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    Meeting the Demands of IoT Analytics

    The Internet of things (IoT) will potentially bring billions of devices and associated logs into data analytics scenarios. Deep Engine enables MySQL to create rows faster and retrieve information more quickly than InnoDB, bringing the ability to deal with trillions of rows of data to support very large IoT analytical projects, such as worldwide sensor placements or scientific and meteorological research chores.
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    Deep Engine Brings Enterprise Performance to MySQL
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    Deep Engine Brings Enterprise Performance to MySQL

    MySQL deployed on infrastructure-as-a-service (IaaS) platforms is traditionally limited by single thread processing. With Deep Engine, multiple threads allow MySQL to outperform enterprise-grade hosted solutions, such as Amazon RDS (Relational Database Service).
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    IBM IaaS Platforms Offer Enhanced Performance With Deep & MySQL
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    IBM IaaS Platforms Offer Enhanced Performance With Deep & MySQL

    Deep Engine enables MySQL to leverage IBM and Zenith IaaS platforms using bare metal server implementations. The combination of hosted platforms along with bare metal servers allows Deep Engine to bring enterprise-level performance to MySQL, while still outperforming fully hosted Amazon RDS implementations.
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    Deep Engine Increases Value of MySQL Databases
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    Deep Engine Increases Value of MySQL Databases

    Performance testing shows that Deep Engine brings increased value to MySQL databases by helping to reduce storage needs while increasing performance and offering higher scale. Deep Engine accomplishes all of that with an easy-to-install plug-in that can be used in conjunction with existing storage engines or used as a replacement for a storage engine.
 

Deep Information Sciences has launched Deep Engine, a plug-and-play storage engine that brings scale and performance to MySQL databases, without the need for recoding or redeploying applications that use MySQL as a data source. What's more, Deep Engine is installed as a simple 10M-byte plug-in, which can run alongside other storage engines or replace them entirely. Deep Engine brings hybrid transactional and analytical processing (HTAP) capabilities to MySQL, making it suitable for big data and other data-intensive projects that require billions of rows of information in both structured and unstructured record formats. Substantial performance improvements and exponentially greater levels of scale are offered, thanks to compression technology, as well as machine learning routines that leverage intelligent heuristics to better organize queries and storage elements. Taken altogether, Deep Engine can potentially delay or prevent the need to transition to more expensive server and database platforms to handle big data or other data-intensive projects.

 
 
 
 
 
Frank Ohlhorst Frank is an award-winning technology journalist, professional speaker and IT business consultant with over 25 years of experience in the technology arena. He has written for several leading technology publications, including ComputerWorld, TechTarget, PCWorld, ExtremeTech, Tom's Hardware and business publications, including Entrepreneur, Forbes and BNET. Ohlhorst was also the Executive Technology Editor for Ziff Davis Enterprise's eWeek and formerly the director of the CRN Test Center.
 
 
 
 
 
 

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