Operational Intelligence: Now Possible Using Hadoop MapReduce
Run Hadoop MapReduce on Live, Operational Data
Take advantage of your experience and expertise in Hadoop MapReduce to easily implement operational intelligence on live data. ScaleOut hServer is the world’s first in-memory execution platform that delivers real-time results on in-memory data without any changes to your MapReduce code. It also allows access to HDFS with built-in HDFS caching and runs Hive queries on in-memory data sets.
The benefits of hServer Include:
- In-Memory Power — ScaleOut hServer’s in-memory data storage and integrated compute engine unlock the power of Hadoop for operational intelligence. Instead of storing live fast-changing data on disk within HDFS, ScaleOut hServer uses a fast, scalable in-memory data grid (IMDG) that enables live data to be continuously saved, updated, and analyzed using ScaleOut hServer’s Hadoop MapReduce compute engine. Standard MapReduce applications now can analyze live, fast-changing data with extremely low latency.
- Fast Deployment — Forget the complexities of installing and configuring complex Hadoop distributions. Because ScaleOut hServer uses its own MapReduce compute engine, it does not require a Hadoop software stack be installed. Instead it ships with all the necessary Hadoop Java API libraries as well as its own open source libraries and server components; everything you need is included. In fact, you can install and start running MapReduce applications on a laptop or developer workstation in under thirty minutes.
- Easy Integration — ScaleOut hServer is compatible with the latest versions of most popular Hadoop platforms, including Apache, Cloudera, Hortonworks, and IBM; ScaleOut Software is a certified Cloudera and Hortonworks partner. This means that you can run fully compatible MapReduce applications for any of these platforms on ScaleOut hServer’s in-memory compute engine.
An overview of StateServer's capabilities includes:
- Open Source Client - ScaleOut hServer’s Java client libraries are available as an open source project at GitHub and are designed to work with ScaleOut’s in-memory data grid and integrated MapReduce compute engine.
- Free Community Edition - ScaleOut hServer can be used at zero cost either for evaluation or production on up to four servers with up to 256GB of data, fully supported by the ScaleOut Community Forum.
- Analyze Live Data - ScaleOut hServer’s in-memory data grid stores key/value pairs across an elastic set of networked servers, ensuring fast data access and updates to live data with linear scalability, and high availability using a standard, object-oriented model.
- Automatic Code Shipping - ScaleOut hServer automatically ships application code to grid servers for execution. You also can optionally use ScaleOut ComputeServer’s “invocation grid” feature to prestage code once and reuse it for multiple MapReduce runs.
- Built-In Scalability and High Availability - As your application workload grows, ScaleOut hServer seamlessly scales its execution throughput as you add servers to the in-memory data grid. This increases storage capacity, access throughput, and execution capacity. The grid automatically redistributes the workload across all servers and keeps execution times fast. ScaleOut hServer’s fully peer-to-peer architecture eliminates bottlenecks to scaling.