Garantia Data, a provider of in-memory NoSQL cloud services, today announced the availability of its Redis Cloud and Memcached Cloud database hosting services on the Windows Azure cloud platform. Garantia Data’s services will provide thousands of developers who run their applications on Windows Azure with virtually infinite scalability, high availability, high-performance and zero-management in just one click.
Garantia is currently offering its Redis Cloud and Memcached Cloud services free of charge to early adopters in the US-East and US-West Azure regions.
Used by both enterprise developers and cutting-edge start-ups, Redis and Memcached are open source, RAM-based, key-value memory stores that provide significant value in a wide range of important use cases. Garantia Data’s Redis Cloud and Memcached Cloud are reliable and fully-automated services for running Redis and Memcached on the cloud – essentially freeing developers from dealing with nodes, clusters, scaling, data-persistence configuration and failure recovery.
“We are happy to be the first to offer the community a Redis architecture on Windows Azure,” said Ofer Bengal, CEO of Garantia Data. “We have seen great demand among .Net and Windows users for scalable, highly available and fully-automated services for Redis and Memcached. Our Redis Cloud and Memcached Cloud provide exactly the sort functionality they need.”
“We’re very excited to welcome Garantia Data to the Windows Azure ecosystem,” said Rob Craft, Senior Director Cloud Strategy at Microsoft. “Services such as Redis Cloud and Memcached Cloud give customers the production, workload-ready services they can use today to solve real business problems on Windows Azure.”
Redis Cloud scales seamlessly and infinitely, so a Redis dataset can grow to any size while supporting all Redis commands. Memcached Cloud offers a storage engine and full replication capabilities to standard Memcached. Both provide true high-availability, including instant failover with no human intervention. In addition, they run a dataset on multiple CPUs and use advanced techniques to maximize performance for any dataset size.
