ScaleOut StateServer®

  • Feature Rich, Battle-Tested, In-Memory Data Grid with a Decade of Development and Support
  • The Scalable, Highly Available, Low-Latency Core of ScaleOut’s Products
  • Industry-Leading Ease of Use that Minimizes TCO

In-Memory Distributed Cache for Scaling Applications

Developing fast, scalable applications on server farms and compute clusters requires that the application’s fast-changing data always be instantly accessible, even as servers are added to handle ever increasing load. ScaleOut StateServer’s in-memory data grid meets this need by keeping data in memory for fast access and using all servers to handle access requests in parallel. With its blazing performance, comprehensive APIs, patented high availability, and self-managing features, ScaleOut StateServer provides the leading in-memory distributed caching solution available today.

Comprehensive Features

With APIs for Java, .NET, & C/C++ and REST, ScaleOut StateServer offers a full range of powerful yet easy to use features for storing and managing memory-based data.



ScaleOut StateServer has been deployed on thousands of servers across hundreds of production systems. Its patented technology delivers industry-leading performance and rock-solid stability.


Architected for Operational Systems

Designed for Managing Fast-Changing Data

Operational systems typically manage huge workloads and need to be able to instantly access fast-changing data, such as web session data, business logic objects, and financial pricing information. ScaleOut StateServer meets this need with an in-memory data grid (IMDG) spanning a cluster of servers and designed to host millions of serialized data objects in memory. Client applications save, access, and update these objects at memory speed using powerful but easy-to-use APIs. This eliminates database bottlenecks, dramatically reduces access latency, and enables automatic scaling to handle growing workloads.

ScaleOut StateServer Runs on a Cluster of Servers

Built to Scale

ScaleOut StateServer automatically scales its storage capacity and access throughput as the application’s workload grows. You simply add a new server to the cluster, and ScaleOut StateServer transparently integrates the new server into the in-memory data grid. It does this by partitioning the stored data and dynamically balancing the amount stored on each server in the grid. This automatically adjusts the relative usage by each server as needed to scale throughput and maintain fast response times. When running ScaleOut StateServer in the cloud, it becomes a fully “elastic” in-memory store — able to expand to handle peak workloads and then shed resources when not needed.

Scales by Adding Servers and Partitioning the Data

ScaleOut StateServer is designed from the inside out to scale every aspect of its architecture and avoid bottlenecks that limit scalability. Performance tests confirm that it delivers consistently fast access times by linearly scaling throughput as servers are added to the in-memory data grid.

Designed for High Availability

Operational systems cannot afford to lose mission-critical data. ScaleOut StateServer ensures that grid-based data is always available — even if a grid server fails — by storing all objects on up to three servers. If a server goes offline or loses network connectivity, ScaleOut StateServer automatically retrieves data from other servers in the grid, and it creates new replicas as necessary to maintain redundant storage. ScaleOut StateServer employs patented “quorum” technology which guarantees that the in-memory data grid always handles server failures correctly and efficiently.

Objects are Replicated for High Availability

To quickly detect and respond to server outages, ScaleOut StateServer uses a patented, scalable heartbeat protocol that triggers an automatic “self-healing” process, which restores access to grid data, rebuilds redundant storage, and dynamically rebalances the workload across the in-memory data grid. Because it automatically handles all aspects of recovery, ScaleOut StateServer simplifies application development and keeps management costs low; you can keep your focus on application development and not be distracted by the details of managing the grid.

Key IMDG Features

Comprehensive, Easy-to-Use APIs

Application developers use application programming interfaces (APIs) to integrate an in-memory data grid (IMDG) into their applications and unlock its power to provide fast data access and seamless scalability. ScaleOut StateServer includes APIs for Java, .NET, and C/C++ applications, as well as as REST APIs that allow integration with almost any programming language. These APIs provide simple, straightforward access to the IMDG for creating, reading, updating, and deleting objects identified by string names or 256-bit numerical keys.

ScaleOut StateServer’s APIs are designed to maximize ease of use while providing advanced, optional features. These include distributed locking, integration with databases and other backing stores, event notifications, parallel query, support for object groups, and much more. New features are carefully added to address customer needs, and ScaleOut StateServer’s APIs represent a decade of close interaction with application developers solving real-world problems.

Parallel Query

Although applications usually identify and access stored objects using unique keys, ScaleOut StateServer includes support for querying the in-memory data grid based on object properties. For maximum query performance, ScaleOut StateServer distributes query processing across all grid servers so that it runs in parallel with automatic scalability and high availability. In addition, object properties can be indexed for fast lookup on each server.

ScaleOut StateServer’s parallel query APIs seamlessly integrate into the Java, C++, and C# languages. Java and C++ applications structure property-based queries using composable filter methods with logical and comparison operators. A full implementation of .NET’s Language Integrated Query (LINQ) enables C# applications to structure queries using SQL-like semantics.


An Example of Property-Based Query

Powerful Feature Set

ScaleOut StateServer incorporates an extensive set of optional features that give application developers the flexibility they need to implement complex operational systems. These features include:

  • Separate namespaces for grouping logically related objects and for optional, extensible authentication/authorization
  • Distributed object locking (optimistic and pessimistic) for synchronizing access by multiple clients and threads
  • Optional object expiration after sliding or fixed timeouts, LRU memory reclamation, or object dependency changes
  • Scalable, highly available asynchronous event handling
  • Optional, fully coherent, “in process” caching of recently accessed, deserialized objects
  • Optional integration with a database server or other backing store
  • Automatic use of language-defined binary formatters and optional, custom serialization
  • Bulk object insertion to add groups of objects with maximum throughput
  • Session-state support for both Microsoft ASP.NET and Java (following the Java 2.5 or 3.0 Servlet specification)

Powerful Management

Self-Managing Features Lower TCO

To make installation quick and keep your management costs low, ScaleOut StateServer employs a wide array of self-managing features. For example, it incorporates a fully peer-to-peer design which avoids the need to deploy and manage a centralized configuration store. Adding a new server to the in-memory data grid is quick and painless thanks to automatic membership detection and load-balancing. Server and/or network outages are automatically handled without the need for management actions.

Powerful Management Tools

ScaleOut StateServer’s centralized management console and command line control program make it easy for IT managers to perform configuration and control tasks from one location and build management scripts. These tools are designed to make it as easy as possible to track the grid’s status, identify issues, and perform management actions. For example, the management console incorporates graphical performance monitoring and a unique “heat map” which graphically displays a color-coded indication of grid activity, load-balancing, and recovery actions.


ScaleOut Management Console Shows Grid Status at a Glance

The optional, ScaleOut Management Pack™ adds more management tools, including an object browser for directly browsing data stored within the in-memory data grid, which assists in both application development and management. The ScaleOut Management Pack also adds a utility for backing up and restoring the contents of the grid. Its fully parallel architecture delivers fast backup/restore times, ensuring that these operations never become a bottleneck as the grid grows to handle large volumes of data.

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