We are launching today the first in-memory NoSQL cloud, which will change the way people use Memcached and Redis. This is a great opportunity to examine the state of these RAM-based data stores and suggest a new, highly-efficient way of operating them in the cloud. Memcached and Redis are being increasingly adopted by today’s web-applications, and are being used to scale-out their data-tier and significantly improve application performance (in many cases improvement is x10 over standard RDBMS implementation). However, cloud-computing has created new challenges in the way scaling and application availability should be handled and using Memcached and Redis in their simple form may not be enough to cope with these challenges. Memcached It’s no secret Memcached does wonders for websites that need to quickly serve up dynamic content to a rapidly growing number of users. Facebook, Twitter, Amazon and YouTube, are heavily relying on Memcached to help them scale out; Facebook handles millions of queries per second with Memcached. But Memcached is not just for giants. Any website concerned with response time and user based growth should consider Memcached for boosting its database performance. That’s why over 70% of all web companies, the majority of which are hosted on public and private clouds, currently use Memcached. Local Memcached is the simplest and fastest caching method because you cache the data in the same memory as the application code. Need to render a drop-down list faster? Read the list from the database once, and cache it in a Memcached HashMap. Need to avoid the performance-sapping disk trashing of an SQL call to repeatedly render a user’s personalized Web page? Cache the user profile and the rendered page fragments in the user session. Although local caching is fine for web applications that run on one or two application servers, it simply isn’t good enough when the data is too big to fit in the application server memory space, or when the cached data is updated and shared by users across multiple application servers and user requests. In such cases user sessions, are not bound to a particular application server. Using local caching under these conditions may end up providing a low hit-ratio and poor application performance. Distributed Memcached tends to improve local caching by enabling multiple application servers to share the same cache cluster. Although the Memcached client and server codes are rather simple to deploy and use, Distributed Memcached suffers from several inherent deficiencies:
Amazon has tried to simplify the use of Memcached by offering ElastiCache, a cloud-based value-added service, where the user does not have to install Memcached servers but rather rent VMs (instances) pre-loaded with Memcached (at a cost higher than plain instances). However, ElastiCache has not offered a solution for any of the Memcached deficiencies mentioned above. Furthermore, ElastiCache scales-out by adding a complete EC2 instance to the user’s cluster, which is a waste of $$ for users who only require one or two more GBs of Memcached. With this model ElastiCache misses on delivery of the true promise of cloud computing – “consume and pay only for what you really need” (same as for electricity, water and gas). Redis Redis an open source, key-value, in-memory, NoSQL database began ramping-up in 2009 and is now used by Instagram, Pinterest, Digg, Github, flickr, Craigslist and many others and has an active open source community, sponsored by VMware. Redis can be used as an enhanced caching system alongside RDBMS, or as a standalone database. Redis provides a complete new set of data-types built specifically for serving modern web applications in an ultra-fast and more efficient way. It solves some of the Memcached deficiencies, especially when it comes to high availability, by providing replication capabilities and persistent storage. However, it still suffers from the following drawbacks:
A new cloud service changes the way people use Memcached and Redis Imagine connecting to an infinite pool of RAM memory and drawing as much Memcached or Redis memory you need at any given time, without ever worrying about scalability, high-availability, performance, data security and operational issues; and all this, with the click of a button (ok, a few buttons). Imagine paying only for GBs used rather than for full VMs and at a rate similar to what you pay your cloud vendor for plain instances. Welcome to the Garantia Data In-Memory NoSQL Cloud! By In-Memory NoSQL Cloud I refer to an online, cloud-based, in-memory NoSQL data-store service that offloads the burden of operating, monitoring, handling failures and scaling Memcached or Redis from the application operator’s shoulders. Here are my top 6 favorite features of such service, now offered by Garantia Data:
We have recently concluded a closed beta trial with 20 participating companies where all these features were extensively tested and verified, – and it worked fine! So this is not a concept anymore, it’s real and it’s going to change the way people use Memcached and Redis! Am I excited today? Absolutely so!
Fig 1– DB Caching Evolution
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