Real-time Analytics

Meetup, MemSQL, ZoomData, Machine Learning

Real-Time Streaming, Analytics, and Visualization with MemSQL and Zoomdata

We regularly host meetups at MemSQL headquarters as a way to share what we have been working on, connect with the community, and get in-person feedback from people like you. We also invite partners and customers to join us as well. Recently, we had the pleasure of hosting a meetup with Zoomdata, where we shared two presentations on real-time streaming, analytics, and visualization using MemSQL and Zoomdata. The first presentation “Streaming in the Enterprise with MemSQL” is presented by...


Direct Employers Case Study

Improving Recruiting Performance with Cloud-Based Real-Time Analytics

About DirectEmployers Association DirectEmployers Association is a nonprofit human resources consortium of leading global employers formed to improve labor market efficiency through sharing best practices. The organization helps companies reduce recruiting costs and ensure regulatory compliance of recruitment programs, such as veteran and public disability requirements. The Impact of Data for Corporate Recruiting The DirectEmployers application collects a variety of data across the web to help...


Data Warehouse Rescue

Seeking a Rescue from a Traditional RDBMS

In the Beginning Years ago, organizations used transactional databases to run analytics. Database administrators struggled to set up and maintain OLAP cubes or tune report queries. Monthly reporting cycles would slow or impact application performance because all the data was in one system. The introduction of custom hardware, appliance-based solutions helped mitigate these issues, and the resulting solutions were transactional databases with column store engines that were fast. Stemming from...


real-time data warehousing

Real-Time Data Warehousing for the Real-Time Economy

In the age of manual decision making based on predictable data formats, data feeds, and batch processing times, enterprise businesses stayed current with ad hoc analyses and periodic reports. To generate analyses and reports, businesses relied on the traditional data warehouse. Using extraction, transformation, and load batch processes, the traditional data warehouse standardized disparate data into normalized schemas and pre-computed cubes. With the data shaped into pre-configured dimensions...


Durable Storage for Real-Time Analytics with MemSQL and Spark

Apache Spark has made a name for itself as a powerful data processing engine for transforming large datasets in a swift, distributed manner. After using Spark to complete such transformations, you often want to store your data in a persistent and efficient format for long-term access. The common solution of storing data in HDFS solves the issue of persistence, but suffers efficiency issues as a result of the HDFS disk-based architecture. The MemSQL Spark Connector solves both of these issues by...


The Analytics Race Amongst The World's Largest Companies

The Analytics Race Amongst The World’s Most Valuable Companies Data is fueling the world’s most valuable companies. Today the list is topped by Apple, Google, Microsoft, Amazon, and Facebook. These top companies harness data to drive outsized value. While the companies are unique, they share a more common approach to analytics than you might expect. The Rapid Rise of Data Capture for Analytics In a short span, entire industries have been born that didn’t exist previously. Each of these...


real-time analytics at UBER

Video: Real-Time Analytics at UBER Scale

At Strata+Hadoop World, James Burkhart, technical lead on real-time data infrastructure at Uber, shared how Uber supports millions of analytical queries daily across real-time data with Apollo, Uber’s internal analytics querying language. James covers architectural decisions and lessons learned from building an exactly-once ingest pipeline that captures raw events across in-memory row storage and on-disk columnar storage. He also details how Uber uses a custom metalanguage and query layer by...


real-time nano marketing

Real-Time and The Rise of Nano-Marketing

The tracking and targeting of our online lives is no secret. Once we browse to a pair of shoes on a website, we are reminded about them in a retargeting campaign. Lesser known efforts happen behind the scenes to accumulate data and scan through it in realtime, delivering the perfect personalized campaign. Specificity and speed are converging to deliver nano-marketing. If you are a business leader, you’ll want to stay versed in these latest approaches. If not, as a consumer, you’ll likely...


Video: Building the Ideal Stack for Real-Time Analytics

Building a real-time application starts with connecting the pieces of your data pipeline. To make fast and informed decisions, organizations need to rapidly ingest application data, transform it into a digestible format, store it, and make it easily accessible. All at sub-second speed. A typical real-time data pipeline is architected as follows: Application data is ingested through a distributed messaging system to capture and publish feeds. A transformation tier is called to distill...


How to Move Analytics to Real Time

How to Move Analytics to Real-Time

3x Spend Increase “Between 2016 and 2019, spending on real-time analytics will grow three times faster than spending on non-real-time analytics.” Every organization uses some form of analytics to monitor and improve their business. The growth of data has increased the impact of analytics and is a critical ingredient for delivering a successful digital business strategy. Companies are using more real-time analytics, because of the pressure to increase the speed and accuracy of...