Blazingly Fast Data Access
+ Simple, Yet Powerful Compute Engine
= ScaleOut In-Memory Computing
ScaleOut Software offers a full range of products for in-memory data storage and computing, stateful stream-processing with the digital twin model, disaster recovery, and global data integration. Below are our four core products available for download, along with additional product options.
By using a fast, C-based implementation of its server architecture, ScaleOut delivers native performance on both Linux-based and Windows operating systems and in mixed configurations.
ScaleOut’s products are available in public clouds including Amazon Web Services and Windows Azure. ScaleOut’s management tools make cloud deployment easy and fast.
Perform Stateful Stream Processing for Deep Introspection
ScaleOut StreamServer™ combines a scalable, stream-processing compute engine with an integrated, in-memory data grid into a powerful, unified software platform for stateful stream-processing. Now you can perform lightning-fast event analysis using sophisticated in-memory state tracking with “digital twin” models to provide deep introspection and precise real-time feedback.
The ScaleOut Digital Twin Builder™ software toolkit dramatically simplifies the development of Java and C#-based digital twin models and their deployment on ScaleOut StreamServer. Digital twin models enable stream-processing applications to track dynamic state information for each data source and analyze its incoming events with a richer context than previously possible. This leads to deeper real-time introspection and better feedback and alerting.
ScaleOut StreamServer incorporates all of the features of ScaleOut ComputeServer, enabling applications to perform data-parallel analyses on live, fast-changing data. This gives applications the ability to immediately detect aggregate trends and generate feedback or alerts. Combined with digital twin models, data-parallel analytics performed in real time offer new insights on the dynamic behavior of data sources that previously were only available with offline, batch processing.
Stateful Stream-Processing with Time Windowing, Kafka and Azure IoT Integration, ReactiveX APIs, and MoreLearn About ScaleOut StreamServer
Stateful stream-processing with digital twins offers deeper introspection than previously possible across a wide range of applications, including financial services, e-commerce, Internet of Things (IoT), medical systems, manufacturing, logistics, and much more.
Here’s just one example: A medical monitoring system can use a dynamic, digital twin model of a patient combined with machine-learning techniques to take into account a patient’s detailed history, medications, and current status when evaluating incoming device telemetry. This allows the system to generate more intelligent and timely alerts to medical professionals.
Unlike mainstream platforms such as Apache Flink, Spark, and Storm, ScaleOut StreamServer automatically dispatches incoming streaming events to in-memory, object-oriented, digital twin models of data sources for analysis. Other platforms need to pull state information from remote data stores, such as database servers and distributed caches; this creates delays and network bottlenecks. ScaleOut StreamServer processes incoming data streams within digital twins stored in an in-memory data grid — where the data lives — ensuring minimum access latency and peak stream-processing throughput.
Analyze Your Live Data for Operational Intelligence
ScaleOut ComputeServer combines distributed, in-memory storage with a scalable compute engine to enable blazingly fast, data-parallel computation on live, fast-changing data. This gives you “operational intelligence” – the ability to analyze data in real time and provide immediate insights and feedback within live, operational systems. Now you can capture perishable business opportunities in your live data as they happen.
Fast Results for Live Data, Scalable Performance, Intuitive APIsLearn About ScaleOut ComputeServer
ScaleOut ComputeServer brings the power of data-parallel computing to distributed, in-memory data. Its compute engine minimizes data motion and delivers blazingly fast execution times. ComputeServer uses techniques from parallel supercomputing, such as multicast and global combining, to deliver results as fast as possible. These capabilities are integrated into an intuitive, easy to use SDK with automatic code shipping that makes application development in Java, C#, and C/C++ simple and straightforward.
Unlike in-memory computing platforms that focus on analyzing streams of data, ScaleOut ComputeServer was specifically designed for operational intelligence within live systems. Its object-oriented, in-memory data storage lets you create a scalable, highly available model of real-world entities (such as portfolios, e-commerce shoppers, or the Internet of Things) which easily can be updated as changes occur. Data-parallel computing enables fast analysis to detect emerging patterns and generate immediate feedback. You have a mission-critical system, and now you have the operational intelligence you need for peak performance.
A Feature Rich, Battle-Tested, In-Memory Data Grid with Java, .NET, C/C++, and REST APIs
Scale your application’s performance with a production-proven, in-memory data grid for both Linux and Windows that delivers fast data access with industry-leading performance and ease-of-use, integrated high availability, powerful APIs, and comprehensive management tools. Deployable both on-premise and on public clouds, ScaleOut StateServer incorporates a decade of technology development and has been put to the test across a wide variety of industries and use cases.
The Industry Standard for High Performance, Ease of Use, and PortabilityLearn About ScaleOut StateServer
Scalability is in our DNA. Every aspect of our in-memory data grid’s architecture is designed to deliver linearly scalable performance with integrated high availability. This means that you can add servers to meet the demands of your business and always expect fast response times in accessing your data. If and when server failures occur, our patented technology ensures that your data will be there and your data grid will recover fast and reliably.
Whether it’s deploying and managing a ScaleOut cluster or developing a new application, we make ease of use a top priority for our products. Our goal is to take care of the grid’s inner workings and keep the APIs as simple as possible so that you can focus on your application’s structure and performance. ScaleOut StateServer automates cluster membership, data partitioning, and load-balancing, and it self-heals with automatic rebalancing after a server failure.
A Simplified and Streamlined Version of ScaleOut StateServer®, Created for Managing ASP.NET Session-State In Memory - Fast
Manage ASP.NET session-state with extremely low-latency, linear scalability, and high availability. Take advantage of the power of an industry-leading, in-memory data grid with a one-line change to your ASP.NET configuration.Learn About ScaleOut SessionServer
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.
Operational Intelligence: Now Possible Using Hadoop MapReduceLearn About ScaleOut hServer
You’ve made an investment in MapReduce and Hive, but with traditional Hadoop you can only realize that investment in batch processing on static data sets. With ScaleOut hServer, you can run MapReduce or Hive on both HDFS data and fast-changing, in-memory data. Sub-second scheduling time and numerous optimizations for real-time execution (such as optional sorting) ensure fast results. Benchmark results have demonstrated 40X speedup and faster.
Installing Hadoop and tuning applications for high performance can be challenging. Sidestep the complexity with ScaleOut hServer. Install it on a cluster of commodity servers – or even your laptop – and run your first MapReduce application in minutes. Self-tuning for in-memory data ensures peak performance. ScaleOut hServer is compatible with the most popular Hadoop distributions, including Apache, Cloudera, and Hortonworks. Use Hadoop YARN to run both in-memory MapReduce/Hive and standard batch processing in one, integrated deployment.
Seamlessly extend ScaleOut StateServer’s in-memory data grid across multiple, geographically distributed data centers to protect against loss of data due to a site-wide outage. Combine multiple data grids across remote data centers into a single, virtual data grid spanning all sites. ScaleOut GeoServer gives you both, and it delivers the scalability and ease of use you expect from ScaleOut Software.
Disaster Recovery and Global Data Integration in One PackageLearn About ScaleOut GeoServer
With ScaleOut GeoServer you can automatically replicate data as it changes among up to eight data centers to protect against data center-wide outages. It’s easy to set up and manage, and it supports “master-master” usage for maximum cost-effectiveness. ScaleOut GeoServer delivers scalable throughput that automatically grows as you add servers to each data center, and it automatically handles server failures. This product has been battle-tested by some of the world’s leading e-commerce sites.
ScaleOut GeoServer can combine your in-memory data grids at multiple data centers, both on-premise and cloud-based, into a single, logical data grid. We call this global data integration, and it dramatically simplifies your application, letting it transparently access data when needed from any location. It even supports distributed locking across sites so that you can globally synchronize updates.