Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Sesame Software Awarded Two New Patents for Data Warehouse Automation

Sesame Software, the innovative leader in Enterprise Data Management, announced two new patents awarded for its Relational Junction data warehouse automation and SaaS data recovery technology. This brings Sesame’s proprietary technology portfolio to nine awarded patents and six pending patents.

Related Posts
1 of 40,680

“These patents are essential to Sesame’s leadership in building instant data warehouses and being able to recover SaaS data without a time-consuming project. Relational Junction does everything for you – there is no project. Simply put, there is no other solution that can match the time to deliver a working warehouse, the level of automation, the speed of loading, and the number of endpoints supported,” says Rick Banister, CEO and Founder of Sesame Software.

Recommended AI News: Agora Data Announces the Release of AgoraInsights

Data Warehouse Loading Performance Improvements

United States Patent 10,003,634 further improves the art of multi-threaded loading of a relational database from a source application by storing the record identifiers that meet a specified query range or filter, multi-threading readers on the content, saving the records in memory, and writing the records from memory into a database.

The scalability and performance of this technique allows massive amounts of data to be loaded quickly and with full restartability in the event of a failure. Customers with hundreds of millions of records benefit from extremely fast throughput, with many threads handling federated loading of a single object in the Cloud to the warehouse. The techniques described in the patent have improved the throughput of Relational Junction by 100 times since the original design in 2004.

Recommended AI News: SQream Offers Free Licenses to Organizations Using Data Analytics to Fight the Coronavirus

SaaS Data Recovery

United States Patent 10,540,237 provides a user interface and internal methods to recover complex relational data to a cloud or on-premise business application. The techniques allow a global recovery, subsetting the data by object name, time range, and record filters, restoring child records automatically, and recovering past versions of records, all in a user-friendly web interface.

Competing products use either a daily flat-file backup or a database backup with a single version of each record. Relational Junction uses primary and secondary backup tables, with the secondary table holding all prior versions. There is never a need for full backups after the initial load, and every version of every record is maintained without having to retain full daily backups for years. A new Recovery Interface is now included in the product for select SaaS applications, such as Salesforce.

Recommended AI News: commercetools Launches Accelerator to Roll out Enterprise Commerce Initiatives Within Two Weeks

Comments are closed, but trackbacks and pingbacks are open.