Tag: transactions

Feed: Planet MySQL; Author: Mark Callaghan; This has results for IO-bound Linkbench on a large server. I previously shared results for in-memory & low-concurrency Linkbench.tl;drCompression doesn't hurt MyRocks performance MyRocks matches or beats InnoDB performance with much better efficiency ConfigurationI used my Linkbench repo and helper scripts to run sysbench with maxid1=1B, loaders=4 and requestors=16 so there will be 4+1 concurrent connections doing the load (4 for link/count tables, 1 for node table) and 16 connections running transactions after the load finishes. My linkbench repo has a recent commit that changes the Linkbench workload and results with that change are labeled new config while results without the change ... Read More

Feed: Latest imported feed items on Analytics Matters. From online browsing to email offers, from in-app shopping carts to in-store purchases, tracking the customer experience is a complex marriage of a myriad of touch points, occurring across endless platforms with countless key performance indicators nested in each. For executives to to really wrap their heads around all these collective data points, there needs to be clear direction over who owns the customer experience. And not a moment too soon: 52 percent of customers have switched providers in the last year based on poor customer service, representing a total of $1.6 ... Read More

Feed: Percona Database Performance Blog. Author: Yves Trudeau. Yves Trudeau  | September 15, 2017 |  Posted In: High-availability, Maxscale, MySQL, ProxySQL PREVIOUS POST This post is the third of a series focusing on the MySQL high availability solutions available in 2017. The first post looked at the elders, the technologies that have been around for more than ten years. The second post talked about the adults, the more recent and mature technologies. In this post, we will look at the emerging MySQL high availability solutions. The “baby” MySQL high availability solutions I chose for the blog are group replication, proxies and distributed storage ... Read More

Feed: Planet big data. Author: JeanFrancoisPuget. Machine Learning and Deep Learning are very promising technologies.  Every week comes with its new hyped successes.  Yet, when it comes to applying machine learning and deep learning many people keep making the same mistakes.  Here is one that is particularly troublesome: people often miss that you need to provide examples to learn from.  They expect systems to learn from raw data without any supervision or feedback.  I can't blame them, as many proponents of machine learning, deep learning, or artificial intelligence just speak about how systems learned from data, without entering the gory ... Read More

Feed: Cambridge Intelligence. Author: Andrew Disney. In the first of three blog posts, we explore the real world applications for graph visualization, starting with law enforcement and fraud management.Use cases for graph visualization“Data is the new oil”– it may be a cliche, but it’s true. Like oil, data in its raw, unrefined form is pretty worthless. To unlock its value, data needs to be refined, analyzed and understood.You can say the same about graphs. More and more organizations are seeing potential in their data connections. The question is, how do you get non-experts to analyze graphs at scale and understand ... Read More

Feed: Big Data Made Simple - One source. Many perspectives.. Author: Baiju NT. Since its launch as the core technology of Bitcoin, blockchain stirred the minds of developers, marketers, and technicians. Other virtual currencies followed its pattern and as a result the total market value of virtual money exceeded 100 billion this summer. Company owners, governments, and specialized institutions are currently facing an alternative financial system which continuously develops and extends. The business world is trying to make the most of it. New possibilities of using blockchain innovation have been tested and implemented, while others are still being researched.  The ... Read More

Feed: MemSQL Blog. Author: Gary Orenstein. The Current Organizational Data Dilemma Today, many companies have years of investment in traditional databases from Oracle, SAP, IBM, Microsoft and others. Frequently these databases and data warehouses have long outlived their ability to cost-effectively perform and scale. These solutions also offer mixed options when it comes to cloud deployments. Over the past decade, data-driven organizations looked to new methods such as Hadoop and NoSQL to solve data challenges. Hadoop has proven to be a good place to store data, but a challenging place for production data workflows. Gartner noted at a recent conference ... Read More

Feed: All - O'Reilly Media. Author: Jana Eggers. Infinity Bridge (source: Victoria Johnson on Wikimedia Commons) Check out Jana Eggers’s sessions, “AI for business” and “It’s the organization, stupid” at the Artificial Intelligence Conference, September 17-20, 2017, in San Francisco to learn more about implementing AI in your organization. Registration is now open. Like infinity, artificial intelligence is an abstract concept. AI commercials show floating orbs and a sprinkling of fairy dust providing magical answers to our questions—even those we didn’t know to ask. These presentations of AI remind me of an episode from South Park’s second season called “Underpants ... Read More

Feed: Planet MySQL; Author: Mark Callaghan; After a few weeks of sysbench it is now time for more complex workloads and the first one is Linkbench with a cached database and low-concurrency. I prefer to start with cached & low-concurrency configurations before trying IO-bound & high-concurrency.tl;dr:InnoDB from MySQL 5.6 had the best throughput CPU efficiency is similar for MyRocks and InnoDB There is a CPU regression from MySQL 5.6 to 5.7 to 8.x Write efficiency was similar for all engines on the load test but much better for MyRocks and TokuDB on the transaction test. ConfigurationI used my Linkbench repo ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Noah Data. Opportunities for Big Data AnalyticsRecently, a consortium of 47 Japanese banks signed up with a blockchain startup called Ripple to facilitate money transfers between bank accounts using blockchain. The main reason behind the move is to perform real-time transfers at a significantly low cost. One of the reasons traditional real-time transfers were expensive was because of the potential risk factors. Double-spending (which is a form of transaction failure where the same security token gets used twice) is a real problem with real-time transfers. With blockchains, that risk is largely avoided. Big data ... Read More