Scaling software today announces support for Redis clients in ScaleOut StateServer® Version 5.11 as a Community Preview. With this release, Redis users can leverage the company’s flagship distributed caching product to connect to a cluster of ScaleOut servers and run Redis commands. This open-source Redis software integration with ScaleOut StateServer adds breakthrough functionality for Redis users by dramatically simplifying cluster management, enabling seamless throughput scaling, and automating recovery from server and network failures. . Aimed at enterprise users, ScaleOut StateServer now offers significant new features and the potential for substantial cost savings over competing commercial Redis products.
Redis clients can connect to a ScaleOut StateServer cluster the same way they connect to a Redis cluster and using the same RESP protocol. This release implements all Redis data structures (strings, sets, sorted sets, lists, and hashes), as well as transactions, publish/subscribe commands, and utility commands. This release does not include support for streams, modules, LUA scripts, and AOF persistence. Redis support integrates open source Redis version 6.2.5 code to process Redis commands, and offers the ability to run on Linux or Windows servers.
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Unlike open source Redis, ScaleOut StateServer implements fully consistent updates to stored data. Additionally, ScaleOut StateServer’s native APIs run alongside Redis commands and incorporate advanced features, such as data-parallel computing, streaming analytics, and consistent and extensive data replication not available on open-source Redis clusters.
Key features include:
- Real Redis open source code: ScaleOut StateServer has integrated Redis version 6.2.5 into its software architecture to manage stored data as a single Redis database and execute all Redis commands. The results produced by Redis commands are identical to those of an open source Redis server.
- Significantly simplified and improved cluster management: ScaleOut StateServer automatically handles all cluster operations, including hash location creation, load balancing, data replication, fault detection, and recovery. It distributes Redis hashslots across a cluster of servers and redistributes them as servers are added or removed. It also uses fully consistent cluster membership to detect server or network failures, rebalance workloads across surviving servers, and create additional replicas to maintain redundancy of stored data.
- Advanced customer management: ScaleOut StateServer simplifies client applications by always providing clients with accurate information about the location of hashslots. It automatically blocks client commands while hashslots are in motion to avoid client-side exceptions and ensure clients always see a transparent cluster view.
- Multi-threaded architecture: ScaleOut StateServer’s multi-threaded architecture automatically uses all processing cores to speed up execution of Redis commands. This eliminates the single-threaded bottleneck created by Redis’ event loop architecture and avoids the complexity of deploying additional “shards” to increase throughput on each server.
“We are excited to provide a new runtime platform to Redis customers with ScaleOut StateServer to meet the needs of enterprise users,” said Dr. William Bain, CEO and Founder of ScaleOut Software. “By incorporating this technology, Redis users can take advantage of ScaleOut StateServer’s industry-leading cluster management capabilities to both reduce operational costs and achieve full consistency for stored data.
Benefits of supporting Redis on ScaleOut StateServer
Integrating Redis into ScaleOut StateServer provides these key benefits:
- Proven software architecture: Developed over 19 years and proven in hundreds of mission-critical deployments, ScaleOut StateServer’s software technology was designed from the ground up for seamless throughput scaling with built-in high availability and maximum ease of use . In contrast, Redis was designed as a single-server data structure store and then enhanced to add clustering features.
- Full data consistency: Unlike Redis clusters, which use an eventual consistency model to update stored data, ScaleOut StateServer implements full data consistency using a patented quorum-based algorithm. This ensures that the caching cluster never serves stale data after a server failure and meets the needs of business-critical operations.
- Transparent throughput scaling: Using a multi-threaded software architecture to run Redis commands, ScaleOut StateServer automatically scales its performance to take advantage of the processing cores on each server. In contrast, Redis uses a single-threaded event loop and requires multiple “shards” to be deployed on each server to increase processing throughput.