{"id":3337,"date":"2023-01-23T16:12:18","date_gmt":"2023-01-23T15:12:18","guid":{"rendered":"https:\/\/www.euroccitaly.it\/?p=3337"},"modified":"2023-12-19T16:27:06","modified_gmt":"2023-12-19T15:27:06","slug":"high-performance-data-management-on-hpc-infrastructure","status":"publish","type":"post","link":"https:\/\/euroccitaly.it\/en\/case-histories-en\/high-performance-data-management-on-hpc-infrastructure\/","title":{"rendered":"High-Performance Data Management on HPC Infrastructure"},"content":{"rendered":"

Industrial organisations involved<\/strong><\/h2>\n
<\/figure>\n

\"\"

Cherrydata<\/a><\/b> is a start-up that offers technology and solutions for highperformance data intelligence, with exceptionally fast response time and extremely low hardware
\n(HW) requirements.
\nThis performance edge is granted by AyraDB<\/a>, a next-generation database<\/strong> with outstanding performance and scalability.
\nThis allows Cherrydata\u2019s customers to work on their business KPIs with no technical or economic scalability limitations. It also reduces energy consumption, with a positive environmental impact<\/p>\n

\"\"

Technical\/scientific Challenge<\/strong><\/h2>\n

To enable a variety of big data applications<\/strong>, the market needs highly efficient data management technologies<\/strong>: satellite data are notoriously big<\/strong>, raising challenges not only from the perspective of analytic applications, but also to be efficiently stored and retrieved.<\/p>\n

AyraDB<\/a><\/strong> was designed to address these challenges.<\/strong><\/p>\n

The goal of the present research is to perform a large-scale test of AyraDB on Davinci-1 supercomputer, belonging to Leonardo Company<\/a><\/strong>.<\/p>\n

These tests can act as a Proof of Concept (PoC) of thetechnical features of AyraDB and of its suitability for challenging applications.<\/p>\n

\"\"

The Solution<\/strong><\/h2>\n

Tests were performed on Davinci-1 with a total of 500 runs on a number of 8-core servers growing <\/strong>from 1 to 20, a data size growing from 10 GB to 500 GB<\/strong>.<\/p>\n

Results show that AyraDB reaches 106 requests\/s with 13 servers<\/strong>, with consistent read\/write performance, beating the state of the art by a 5x factor<\/strong>.<\/p>\n

AyraDB has not only best-in-class cost-to-performance ratio<\/strong>. Tests demonstrated that it has linearly scalable performance<\/strong>: if HW capacity doubles, AyraDB\u2019s performance doubles. Competing solutions require more than double capacity to double performance.<\/p>\n

Above a certain threshold, their performance stops increasing even if the infrastructure provides additional capacity, the database cannot exploit it.<\/p>\n

In fact, AyraDB can use additional capacity with no upper bounds to scalability.<\/strong><\/p>\n

\"\"

Business impact<\/strong><\/h2>\n

The PoC has provided third-party performance benchmarks<\/strong>. Obtaining third-party performance benchmarks is a time-consuming and costly activity and the PoC has provided these benchmarks,
\nacting as proof of the performance of AyraDB beyond Cherrydata\u2019s own claims.<\/p>\n

This is clearly important for Cherrydata<\/strong> and can boost adoption by helping overcome the skepticism that is inevitably associated with a new technology. In the context of an IT deep tech is even more critical<\/strong>. The quasi monopoly of global cloud providers and their aggressive marketing have created the belief that they provide the best possible technology.<\/p>\n

With this PoC, it was proved that it is possible to substantially improve the quality of cloud services and that greater performance can be obtained with a technology architecture that makes a better use of RAM and, thus, reduces costs by a factor of 20.<\/strong><\/p>\n

\"\"

The benefits<\/strong><\/h2>\n
    \n
  • Performance improvement of data management<\/li>\n
  • Cost reduction of cloud services<\/li>\n
  • Enabling technical and economic feasibility of several big data applications<\/li>\n
  • Energy savings<\/li>\n<\/ul>\n

    Images Courtesy: Cherrydata<\/p>\n","protected":false},"excerpt":{"rendered":"

    To enable a variety of big data applications, the market needs highly efficient data management technologies: satellite data are notoriously big, raising challenges not only from the perspective of analytic applications, but also to be efficiently stored and retrieved.
    \nAyraDB was designed to address these challenges. <\/p>\n","protected":false},"author":1,"featured_media":7574,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[13],"tags":[],"class_list":["post-3337","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-case-histories-en"],"_links":{"self":[{"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/posts\/3337","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/comments?post=3337"}],"version-history":[{"count":27,"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/posts\/3337\/revisions"}],"predecessor-version":[{"id":8316,"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/posts\/3337\/revisions\/8316"}],"wp:attachment":[{"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/media?parent=3337"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/categories?post=3337"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/euroccitaly.it\/en\/wp-json\/wp\/v2\/tags?post=3337"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}