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December 22, 2011 | Jim Tommaney

A Behind the Scenes look at InfiniDB: Parallelism (Part 2 of 3)

Jim Tommaney, Chief Technology Officer, Calpont

As part of a second post in our three-part series, we'd like to discuss the importance of parallelism and how InfiniDB uses parallelism to achieve breath taking performance.

InfiniDB is architected for effortless scalability.

The InfiniDB database is comprised of two types of modules: User Modules and Performance Modules. User Modules interpret MySQL commands and convert them into parallelized code for execution.

Performance Modules execute the parallelized code and return the result to the User Modules. Performance Modules are architected to be lightweight and to execute in a MapReduce-fashion, similar to Apache Hadoop. (To be clear, though, Performance Modules do not use Hadoop code. In fact, we started designing this architecture well before Hadoop/HDFS’ adoption.)

Our customers typically have one or a few User Modules, although customers may use any number of User Modules to provide high-availability and workload balancing. In a distributed environment, one or more User Modules may be interacting with any number of Performance Modules.

Due to InfiniDB's Map-Reduce-like scale-out architecture, our Performance Modules execute requests extremely effectively.   Each thread within the distributed architecture operates independently, avoiding thread-to-thread or node-to-node communication that can cripple scaling.

What this means for our customers is that InfiniDB scales linearly. In internal tests, we've scaled InfiniDB on Amazon EC2 to 1024 cores without noticeable loss in performance. In fact, we believe that we can scale to 1 Million cores (although our customers have not yet asked us for deployments of this size).

The impact of this is groundbreaking. Large deployments, such as companies delivering analytics over the Cloud, require extremely efficient databases to enable their customers’ needs. Lightweight chips, such as mobile processors and GPUs, also need efficient databases due to hardware constraints. Companies with massive amounts of data (such as Petabyte-size data volumes) need highly-efficient technology to enable analytics their data. InfiniDB's architecture remains performant under all of these scenarios.

Stay tuned for the third post in this three part series, where we discuss the unparalleled ease-of-use with which our customers use InfiniDB.

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