real-time

real-time predictions

Predictions 2016: the Impact of Real-Time Data

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 a price: time. While the goal of machine learning is to develop models that will prove useful, dealing with large...


Modern Database Characteristics

Characteristics of a Modern Database

Many legacy database systems are not equipped for modern applications. Near ubiquitous connectivity drives high-velocity, high-volume data workloads – think smartphones, connected devices, sensors – and a unique set of data management requirements. As the number of connected applications grows, businesses turn to in-memory solutions built to ingest and serve data simultaneously. Bonus Material: Free O’Reilly Ebook – learn how to build real-time data pipelines with modern...


Case Study: How Tradelab Enables Real-Time Bidding with MemSQL

Tradelab, a programmatic marketing platform company based in France, uses MemSQL to process and analyze real-time bidding data for hundreds of customers. Challenge: NoSQL Data Latency The Tradelab real-time ad serving platform requires a heavy mixed read/write workload, and the NoSQL database they had in place was introducing unnecessary data latency into the ad-bidding process. The company began searching for a replacement – a true real-time data management solution with two key...


O'Reilly Webcast

Building Real-Time Data Pipelines through In-Memory Architectures [Webcast]

In the era of universal connectivity, the faster you can move data from point A to B the better. Equipping your organization with the ability to make frequent decisions in an instant offers information and intelligence advantages, such as staying one step ahead of the competition. This is especially important when incoming data is arriving at a relentless pace, in high volume, and from a variety of devices. As our customers tap into new sources of data or modify to existing data pipelines, we...


Market Making with MemSQL: Simulating Billions of Stock Trades in Real Time

I woke up around 7:30 AM on Monday August 24th, checked my phone while lying in bed, and saw that I had lost thousands of dollars in my sleep. Great way to start the week… I was not alone – few investors escaped “Black Monday” unscathed. The past several months have been full of sudden surges and declines in stock prices, and extreme volatility is apparently the “new normal” for global financial markets. Frequent and dramatic market swings put a high premium on access to...


Spark Streamliner

Build Real-Time Data Pipelines with MemSQL Streamliner

MemSQL Streamliner is now generally available! Streamliner is an integrated MemSQL and Apache Spark solution for streaming data from real-time data sources, such as sensors, IoT devices, transactions, application data and logs. The MemSQL database pairs perfectly with Apache Spark out-of-the-box. Apache Spark is a distributed, in-memory data processing framework that provides programmatic libraries for users to work with data across a broad set of use cases, including streaming, machine...


Geospatial Real-Time Apps

Locate This! The Battle for App-specific Maps

In early August, a consortium of the largest German automakers including Audi, BMW, and Daimler (Mercedes) purchased Nokia’s Here mapping unit, the largest competitor to Google Maps, for $3 billion. It is no longer easy to get lost. Quite the opposite, we expect and rely on maps for our most common Internet tasks from basic directions to on-demand transportation, discovering a new restaurant or finding a new friend. And the battle is on between the biggest public and private companies in the...


in-memory database survey

In-Memory Database Survey Reveals Top Use Case: Real-Time Analytics

To shed light on the state of the in-memory database market, we conducted a survey on the prevalent use cases for in-memory databases. Respondents included software architects, developers, enterprise executives and data scientists1. The results revealed a high demand for real-time capabilities, such as analytics and data capture, as well as a high level of interest in Spark Streaming. Real-Time Needs for In-Memory Databases It is no surprise that our survey results highlight real-time...


Tapjoy is Powering its Mobile Ad Platform with MemSQL

Over the past several months, we worked closely with the Tapjoy data science and engineering team to implement MemSQL as the database to power their Mobile Marketing Automation and Monetization Platform. In order to deliver optimized ads to over 500 million global users and support over one million transactions per minute, Tapjoy needed a database that could enable HTAP, a Gartner term we refer to frequently at MemSQL, which stands for Hybrid Transactional and Analytical Processing. Two Use...