Harness Big Data with Scalable Cloud Solutions
Volume, velocity, and variety make big data hard to capture, expensive to store, and very difficult to analyze. Traditional RDBMS were originally designed to work with a fraction of the current data loads, which now results in performance and scalability issues.
Start with a small cluster and scale to hundreds of nodes
Having extensive experience in optimizing large-scale distributed solutions for data mining, analysis, etc., Altoros can help you build a system capable of capturing, storing, and analyzing huge amounts of data. You can optimize your database to sustain extreme loads and grow along with your data processing needs.
|Test and fine-tune your data-driven system||Find performance issues by simulating extreme data loads. Get faster reads/writes by fine-tuning your solution. Speed up data processing by distributed computing.|
|Turn big data into value||Uncover dependencies and opportunities hidden in your big data with data modeling and custom algorithms.|
|Scale as you grow||Migrate to the cloud for better scaling: quickly expand or shrink your cloud storage as your needs change. Automate deployment and maintenance of your database.|
10+ years of experience in building complex systems
- Extensive experience in MongoDB, Cassandra, HBase, Couchbase, Riak, Amazon Dynamo, Google BigTable, and other NoSQL/NewSQL systems
- Vast expertise in building large-scale distributed computing solutions—the largest cluster deployed by Altoros’s engineers consisted of 400+ nodes
- Our R&D engineers have performed multiple benchmark studies of NoSQL and cloud solutions published by CIO.com, NetworkWorld, ComputerWorld, TechWorld, and other industry magazines
- A 250+ strong full-time team with hands-on expertise in building core big data technologies for RightScale, NuoDB, Couchbase, and other technology vendors