Top Stream Processing Questions Answered by the Experts [Hive Panel Recording]

By Serena Malkani on January 28th 2016 in Events

The Hive think tank recently held a panel discussion on Stream Processing Systems. Panelists debated best approaches to messaging platforms, stream systems, and accompanying data stores. Other topics included scalability, latency, fault-tolerance/reliability/High Availability, ease and simplicity of deployment, maturity and popularity, enterprise features, and security. There was a lot covered! Ben Lorica, O’Reilly Media’s Chief […]

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The Lambda Architecture Simplified [Guide]

By Kevin White on January 26th 2016 in Lambda Architechture

Modern businesses need to support an increasing variety of data workloads and uses cases that require both fault-tolerance and scalability. This has led to widespread adoption of the Lambda Architecture. Lambda is designed to model everything that happens in a complex computing system as an ordered, immutable log of events. Processing the data (for example, […]

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dbbench: Bringing Active Benchmarking to Databases

By Alex Reece on January 21st 2016 in Engineering

In my last blog post, I investigated a Linux performance issue affecting a specific customer workload. In this post, I will introduce the tool I created to drive that investigation. Recently, a customer was running a test where data was loaded into MemSQL via LOAD DATA. The customer’s third-party benchmarking tool found that MemSQL took […]

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MemSQL Meetups – Year in Review

By Lesia Myroshnichenko on January 20th 2016 in Events

It has been six months since we began hosting meetups regularly at MemSQL. Our office is located in the heart of SoMa, two blocks from the Caltrain station. At the new San Francisco epicenter of tech startups, we want to meet our neighbors and see what other cool technologies are out there! What better way […]

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Choosing the Right Infrastructure for IoT

By Gary Orenstein on January 19th 2016 in In Memory Database, IoT

The infrastructure of IoT will have a real-time database behind every sensor. Soon every device with a sensor will blend seamlessly into the Internet of Things, from drones to vehicles to wearables. Device and sensor count predictions range from billions to trillions. With this tidal wave of new devices comes an increasing number of new […]

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Investigating Linux Performance with Off-CPU Flame Graphs

By Alex Reece on January 7th 2016 in Engineering

The Setup As a performance engineer at MemSQL, one of my primary responsibilities is to ensure that customer Proof of Concepts (POCs) run smoothly. I was recently asked to assist with a big POC, where I was surprised to encounter an uncommon Linux performance issue. I was running a synthetic workload of 16 threads (one […]

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The Lambda Architecture Isn’t

By Carlos Bueno on December 28th 2015 in Lambda Architechture

The surest sign you have invented something worthwhile is when several other people invent it too. That means the creative pressure that gave birth to the idea is more general than your particular situation. Even when faced with the same pressures, people will approach an idea in different ways. When Jay Kreps was developing Kafka […]

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Rethinking Lambda Architecture for Real-Time Analytics

By Dale Deloy on December 23rd 2015 in Case Study, Lambda Architecture, Spark

Big data, as a concept and practice, has been around for quite some time now. Most companies have responded to the influx of data by adapting their data management strategy. However, managing data in real time still poses a challenge for many enterprises. Some have successfully incorporated streaming or processing tools that provide instant access […]

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Predictions 2016: the Impact of Real-Time Data

By Eric Frenkiel on December 22nd 2015 in Analytics, In-Memory, Industry, IoT, real-time

Prediction 1. The industrial internet moves to real-time data pipelines The industrial internet knits together big data, machine learning, and machine-to-machine communications to detect patterns and adjust operations in near real time. Soon the industrial internet will expand by definition to include the Internet of Things. The detection of patterns and insights often comes with […]

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Introducing a Performance Boost for Spark SQL, Plus Python Support

By Emily Friedman on December 16th 2015 in Engineering, Spark

This month’s MemSQL Ops release includes performance features for Streamliner, our integrated Apache Spark solution that simplifies creation of real-time data pipelines. Specific features in this release include the ability to run Spark SQL inside of the MemSQL database, in-browser Python programming, and NUMA-aware deployments for MemSQL. We sat down with Carl Sverre, MemSQL architect […]

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Powering Digital Advertising.

Learn how Ziff Davis uses MemSQL to track and analyze millions of impressions in real time.

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