There are two trends driving the exploding data volumes in the digital and social media world today. First, with the network effect of Metcalfe’s Law, the success of the real-time web in connecting people leads to increased engagement and therefore more data. Second, there is a trend we are calling the Deep Real-Time Web that refers to the machine-to-machine communication resulting from and in fact dwarfing the user-driven interactions. In addition to handling these exploding data volumes, customers who have implemented a Truviso operational analytics solution “democratize the data” by providing a low-latency and high-concurrency environment for interactive queries.
The Truviso Continuous Analytics 3.2 release introduces a highly scalable data-parallel processing architecture that exploits the newest many-core hardware as well as multi-machine cluster configurations. Software needs to be written specifically for multi-core architectures to avoid performance problems; while we did it right, it’s an area where some other software companies stumble, as pointed out in a good Forbes.com article.
Truviso achieves vertical scalability on many-core SMP systems by splitting incoming data into independent streams running an on-the-fly basis so that each run can be processed in parallel and consolidated continuously. This vertical scalability technology lets enterprises save money on hardware, networking, data center and maintenance costs. For example, a large media network with analytics applications running on a 40-node cluster of specialized data warehouse servers each costing over $50,000 successfully offloaded the most high-value and high-volume workloads at 500,000 records/second on one production and one hot failover server running Continuous Analytics — with hardware costs of just $6,500 for each commodity server.
Speaking of hot failover, with version 3.2 you have the option to use a cluster configuration to achieve high availability / disaster recovery (HA/DR), seamless failover and distributed scalability, as well as scale out processing of interactive queries. The clustering infrastructure allows multi-master replication where data can be sent to any node in the cluster. Queries can also be deployed in the system in an active-active fashion to provide instant failover in the event of a node failure. A failed node can be brought back online and transparently start processing the latest data, while automatically and seamlessly “catching up” with the data that it missed during the time it was offline in an asynchronous fashion.
In addition to high availability and failover, this release offers continuous online backup features that can be used to organize a cluster in an active-standby configuration. Together with our TruLink connectors to aggregate data from disparate sources, we provide lots of flexible options to fit seamlessly in your existing infrastructure.
Features and Benefits