StorReduce Product and Features

StorReduce is the only deduplication engine build for cloud object storage. StorReduce is designed to meet the unique requirements of companies using public, private or hybrid cloud storage for large volumes of data. StorReduce sits between your applications and cloud storage, transparently deduplicating data inline at speeds of up to 1400 MB/s per server, reducing storage costs, speeding up the time for transfer between clouds and freeing your data for use in the cloud via standard cloud APIs.

Inline Deduplication

The StorReduce Server sits between client programs (wanting to store and retrieve data) and the Cloud Storage service they are using. It transparently provides best-of-class data deduplication and throughput speeds.

The StorReduce server is optimized for scalability, high throughput and low latency. The internal architecture and code are highly optimized for data deduplication, and to ensure that performance is maintained even when running in a public cloud environment. A single StorReduce server is capable of sustained speeds of up to 1400 Megabytes per second per server, for both reads and writes.

StorReduce can support up to 80 Petabytes of data per server.

Backups

StorReduce makes cloud a more affordable storage medium than tape when it achieves a deduplication ratio of 50%+. This is the case even factoring in migration costs as it greatly reduces the cost for transmission bandwidth and on-cloud storage - StorReduce typically achieves 97% deduplication on backup data.

StorReduce can be installed on-premises to deduplicate data before it is sent to the cloud, often speeding up transfer times 20 - 30x.

StorReduce works with Veritas NetBackup, CommVault, Veeam and other leading enterprise backup solutions.

Data Replication

StorReduce supports replication of deduplicated data between cloud regions, between public clouds or between public and private cloud.

By only replicating the unique data StorReduce can save significant costs on outgoing bandwidth and replica storage, and it often speeds up transfer times 20 - 40x.

A second StorReduce server can be run in the replica region or cloud to enable immediate read-only access to the replicated data. This is perfectly suited for an additional layer of redundancy and for disaster recovery in the cloud.

Big Data

StorReduce's scalability for large data sets and its very fast throughput make it an ideal solution for on-cloud big data companies wanting to decrease their cloud storage and also use data mining services like Elastic, EMR or Hadoop in real time.

Data in StorReduce is accessable by standard cloud object storage interfaces and can be used by any big data or analytics service.

High Availability

High Availability is supported via StorReduce's simple cluster mechanism. StorReduce cluster deployments can be crafted to span cloud availability zones and regions to ensure data access is maintained even in the unlikely event of a complete failure of a cloud datacentre.

StorReduce maintains an index of user data on fast local storage. Each StorReduce server keeps its own independent index. All index data can be rebuilt from the log of transactions stored in Cloud Storage - this enables new StorReduce servers to be started on-premises or on-cloud to quickly access stored data for disaster recovery.

Supported Clouds

The StorReduce server uses Cloud Object Storage for all persistent data. It acts as a client and supports making use of the Amazon S3 REST API or Azure Blob Storage API to store all its data in a single bucket. This means StorReduce may be used with any Amazon S3 or Azure-compatible Cloud Storage solution.

In addition to public Cloud Object Storage solutions, StorReduce works with all major private Object Storage solutions including IBM Cloud Object Storage (formerly Cleversafe), Hitachi Content Platform, HGST Active Archive and SwiftStack.

Officially supported Object Storage services include Amazon S3 (including Glacier and Infrequent Access), Google Object Storage (including Nearline), Azure Blob Storage, IBM Cloud Object Storage, Hitachi Content Platform, HGST Active Archive, Cloudian, Riak CS and SwiftStack..