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Recently, Parse announced they'd be retiring their service entirely on January 28th, 2017. While this comes as a bit of a shock to their own customers and the community as a whole, they're working to ensure that the transition off their platform is a simple process. We at ObjectRocket are doing the same to help any customer find a good home for their MongoDB data! In this post I'll outline how easy it is to move over to the ObjectRocket family and how we can help. Let's jump right in.
Your mobile app's data is hosted on Parse and you just found out that Parse is shutting down. Now what? In this post, I'll cover how ObjectRocket can help support your transition with a fully managed MongoDB solution.
Today we are happy to announce the wider availablity of our fully managed Encryption-at-Rest for ObjectRocket MongoDB in Virginia (IAD), Dallas (DFW), Chicago (ORD), and London (LON). This optional premium feature is availiable on versions 2.6 and 3.0 (mmap or WiredTiger) in both dedicated and shared plans.
If you are looking to take advantage of the Spark's speed and ease of use, you owe it to yourself to try our Rackspace optimized Spark Stack. Spark combined with Tachyon and Zeppelin culminates into a very fast and easy-to-use option. In addition to this stand alone Spark Stack, we also have versions that are bundled with Hortonworks Data Platform, for those wishing to use Hadoop and Spark on the same cluster.
Today I am excited to announce we have added a new capability to our Managed Cloud Hadoop and Spark Service. In the past our users would provision their Hadoop or Spark clusters based on some pre-defined stacks we had created. While this worked for many of our users, there were others that wanted more flexibility and more control. To that end, we have been working for the last year on an entirely new provisioning system that would allow our customers to create fully customized stacks. This now means instead of settling for the default values for number or size of master services nodes, users now have the ability to define the individual node sized and how many of each. You want 3 name nodes instead of 2? No problem. You want 8GB of memory per name node instead of 4? No problem. You want to create a stack that has your ideal configuration of services, such as Spark with Kafka, and Zepplin, but not some of the other components that come by default? No problem.
Our mission at ObjectRocket is to provide the fastest, most reliable databases available. There are plenty of great places to run your applications, but the role that containers (and Docker in particular) play in the enterprise today is undeniable. Rackspace recently released a great new service called 'Carina', providing a high performance hosted Docker Swarm service that complements ObjectRocket very well. In this post, I'd like to show you how to get started deploying and scaling applications on Carina, while easily integrating with blazing fast databases on ObjectRocket.
Since we launched our ObjectRocket Elasticsearch service this past July, we have been hard at work in the garage, wrenching on some new features to add chrome to our Elasticsearch rocket. We are pleased to announce the following new features:
One of the most exciting developments over the lifetime of MongoDB must be the inclusion of the WiredTiger storage engine in MongoDB 3.0. Its very design and core architecture are legions ahead of the current MMAPv1 engine and comparable to most modern day storage engines for various relational and non-relational stores. One of the most compelling features of the WiredTiger storage engine is compression. Let's talk a bit more about performance and compression.