Lambda Architecture

big data changing

From Big to Now: The Changing Face of Data

Data is changing. You knew that. But the dialog over the past 10 years around big data and Hadoop is rapidly moving to data and real-time. We have tackled how to capture big data at scale. We can thank the Hadoop Distributed File System for that, as well as cloud object stores like AWS S3. But we have not yet tackled the instant results part of big data. For that we need more. But first, some history. Turning Point for the Traditional Data Warehouse Internet scale workloads that emerged in the...


lambda architecture

Rethinking Lambda Architecture for Real-Time Analytics

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 to real-time data, but most traditional enterprises are still exploring options. Complicating the matter further, most enterprises need access to...


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...


Lambda Architecture

Real-Time Stream Processing Architecture with Hadoop and MemSQL

With Hadoop Summit Europe underway today, we wanted to share some thoughts on how MemSQL fits in to the Hadoop ecosystem. While MemSQL and Hadoop are both data stores, they fill different roles in the data processing and analytics stack. The Hadoop Distributed File System (HDFS) enables businesses to store large volumes of immutable data, but by design, it is used almost exclusively for batch processing. Moreover, newer execution frameworks, that are faster and storage agonistic, are...