January 13, 2017machine learningMachine Learning,predictive analytics,Predictive Analytics
O’Reilly Media Editor, Jon Bruner, recently sat down with MemSQL VP of Engineering, Drew Paroski, and MemSQL CMO, Gary Orenstein, to discuss the rapid growth and impact that machine learning will have in 2017.
In this podcast, Paroski and Orenstein share examples from companies using real-time technologies to power machine learning applications. They also identify key trends driving the adoption of machine learning and predictive analytics.
Podcast topics of discussion include:
by Nicole Nearhood
January 10, 2017securitySecurity
Today, a number of cyber attacks are carried out by malicious insiders or inadvertent actors. Whether a large government agency or commercial company, protecting your data is critical to successful operations. A data breach can cost significant amounts of lost revenue, a tarnished brand, as well as lost customer loyalty. For government agencies, the consequences can be more severe.
MemSQL has a comprehensive security focus, including the ability to protect sensitive data against the “Insider...
by Mike Mohler
December 23, 2016in-memory,real-timereal-time,In-Memory,In Memory Database,In Memory Database,Real-time Analytics
Adoption of in-memory technology solutions is happening faster than ever. This stems from a three pronged demand – first, a greater number of users, analysts, and businesses need access to data. Second, the number of transactions is increasing globally, so companies need faster ingest and analytics engines. Finally, performance inconsistencies are the nail in the coffin for companies competing in the on-demand economy – these enterprises need the responsiveness in-memory technology...
by Emily Friedman
December 21, 2016in-memory,real-timereal-time
In some industries, a hesitance remains in recognizing the commodification forces of real-time solutions. These industries often rely on orthodox tenets as barriers to marketplace entry, such as regulatory compliance, traditional value propositions, brand recognition, and market penetration. The term “ripe for disruption” often characterizes these industries and their respective leaders.
Arguably, an illustrative industry in the midst of responding to commodification, adapting to real-time...
by Seth Luersen
December 14, 2016IndustrySQL,SQL
The history of SQL, or Structured Query Language, dates back to 1970, when E.F. Codd, then of IBM Research, published a seminal paper titled, “A Relational Model of Data for Large Shared Data Banks.”
Since then, SQL has remained the lingua franca of data processing, helping build the relational database market into a $36 billion behemoth.
The Rise And Fall of NoSQL
Starting in 2010, many companies developing datastores tossed SQL out with the bathwater after seeing the challenges...
by Gary Orenstein
November 29, 2016cloudCloud
Today we announced a brand new managed service, MemSQL Cloud. We look forward to sharing more details with the industry and will be at AWS re:Invent at booth 2820.
We have also put together a few questions and answers below. You can also take a peek at our news release launched today.
Why is the time right for a managed real-time analytics platform-as-a-service?
Application data is being born in the cloud at an ever growing rate. Cloud data is no longer just for media files and backups but...
by Rick Negrin
November 21, 2016real-time,case studyCase Study,Teespring
Teespring is revolutionizing retail, giving entrepreneurs the opportunity to build and grow their brands via its ecommerce platform. Teespring makes it easy for anyone to create and sell high-quality products people love, with no cost or risk. Since 2012, Teespring has shipped more than fifteen million products around the world.
Understanding Real-Time Buyer Activity
Teespring was growing its community at a rapid pace. To further this growth, they wanted to connect vendors with...
by Lesia Myroshnichenko
November 16, 2016Engineeringreal-time,real-time,data movement
Data movement remains a perennial obstacle in systems design. Many talented architects and engineers spend significant amounts of time working on data movement, often in the form of batch Extract, Transform, and Load (ETL). In general, batch ETL is the process everyone loves to hate, or put another way, I’ve never met an engineer happy with their batch ETL setup.
In this post, we’ll look at the shift from batch to real time, the new topologies required to keep up with data flows, and the...
November 15, 2016case studyCase Study,Tableau
Kellogg Company is the world’s leading cereal company, second largest producer of cookies, crackers, and savory snacks, and a leading North American frozen foods company. With 2015 sales of $13.5 billion, Kellogg produces more than 1,600 foods across 21 countries and markets its many brands in 180 countries.
Driving Revenue with Customer Logistics Data
Kellogg relies on customer logistics data to make informed decisions and improve efficiencies around shopping...
by Kevin White
November 11, 2016energyreal-time,Case Study,use case,smart meter,utilities
Smart gas and electric meters produce huge volumes of data. A small MemSQL cluster of 5 nodes easily handles massive quantities of data like the workloads from leading gas and electric utility enterprises.
In one particular use case, over 200,000 meter readings per second load into the MemSQL database while users simultaneously process queries against that data. Millions of meters sending between 10 and 30 sensor readings every hour leading to billions of rows of data. Just an initial part of a...
by Dale Deloy