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Open source: The Best Choice For Big Data

Just 12 months ago, even the largest organisations lacked the infrastructure, tools and skills to turn large datasets into business insight. Today, though, the world has changed. A combination of low-cost, commodity hardware and great open-source software are lowering the Big Data bar for organisations of all types and sizes. Put simply, open-source solutions are allowing organisations to spin up hundreds of servers to support Big Data services in seconds, and pay only for the resources they use.

Here are just a few of the reasons why open-source software is the best foundation for Big Data:

1) Support for the latest Big Data tools

While proprietary operating systems (OSs) are upgraded every two to three years, some open-source OSs offer a much shorter release cycle and longer support periods. This means that all the latest Big Data tools are already supported - from the latest releases of Hadoop and Cassandra, to MongoDB and Couchbase; all the right tools that organisations need to get the most from their data.

2) Cloud compatibility

The best open-source operating systems offer native support for private and public clouds. As well as providing true portability of workloads between private and public clouds, these types of systems support real-time resource provisioning and scaling, with no requirement for per-machine licenses, which also means massive cost savings.

3) Rapid deployment for Big Data infrastructure

The infrastructure that supports Big Data operations must be flexible and easy to deploy. Therefore, it's important to have software that automates the process of installing instances on 'bare-metal' servers and allow computing resources to be dynamically re-purposed to handle different workloads based on changing business needs.

4) Service-oriented development

In the future, developers will think about services, not the underlying infrastructure needed to support them. There are tools available for provisioning services and their underlying infrastructure components. This allows DevOps to deploy Big Data services in a matter of minutes, provisioning and interconnecting all the required infrastructure and apps.

5) No licensing restrictions

Unlike proprietary software, open-source OSs offer a cost-effective way of spinning up Big Data infrastructure, with no need for costly, per-machine licenses. Just make sure the OS you choose is completely free of licensing restrictions.

6) Out-of-the-box hardware support

There are license-free operating systems that are come already certified to run on low-cost, commoditised hardware in the datacentre. This is a key benefit for Big Data, which can require significant computing resources.

Open-source technology is helping organisations of all types and sizes convert massive datasets into meaningful business intelligence. While proprietary systems are expensive to deploy across large, distributed, Big Data environments, open-source software is far less expensive. What's more, it supports real-time scaling of Big Data environments, with no increase in licensing costs.

For these reasons, open-source software is leading the way for Big Data applications. These technologies support effective distribution of NoSQL databases, file systems and innovative Big Data applications such as Hadoop across tens or even hundreds of nodes. What's more, these kinds of systems support true compute and storage elasticity for Big Data platforms, ensuring organisations get the results they need faster.