GPU Databases in action

18th November 2021 by Brytlyt

Seeing something in action is typically a far more valuable experience than just simply having it explained, and once organisations are shown the benefits that can be made by having a GPU-powered database, it creates quite a compelling case for itself.

Going far beyond generating summaries and reports, a GPU database unlocks the ability to visualise enormous amounts of data that can produce business-changing insights within a live environment.

Being able to perform data analysis live, in real time, makes GPU (Graphics Processing Unit) databases revolutionary for both business users and data scientists. By reducing wait times from hours to seconds, GPUs are inherently more efficient, with the added benefit of reducing IT costs and energy consumption.

GPU databases use the power of GPUs to query and analyse enormous amounts of data, returning results with incredible speed. This means that organisations can focus more time on gaining insights, and less time processing queries.

With thousands of GPU cores processing complex computations incredibly quickly, GPUs have an amazing capability to process huge volumes of data in parallel so they’re particularly well suited to non-graphical tasks – even though this functionality wasn’t in the original design remit. In fact, GPU database solutions are moving into many enterprise data centers to replace CPUs (Central Processing Units) as the preferred method of crunching data.

Over the past few years, the GPU database market has expanded rapidly, and GPU-Powered Business Intelligence Tools are now used in a variety of Big Data applications including Machine Learning, Deep Learning, and Advanced Data Science.

The majority of organisations now understand that their data is one of their most valuable assets, but only with the agility to extract and process the information more efficiently, and more broadly, in real time.

As the market for Data Analytics has grown, so have the types of systems on the market – piquing the interest of many organisations that may not have previously considered such systems. Many enterprises now find themselves in the situation where they have a broad range of data, but often miss out on making the most of their data capital.

GPU-accelerated systems are (by their very nature) inherently well-suited to power data visualisation software in real-time for enormous datasets and a truly dynamic analytics experience.

At the forefront of the GPU database revolution

Over time, GPUs have become more flexible and programmable, enhancing their capabilities beyond the gaming sphere. This allowed graphics programmers to create more interesting visual effects and realistic scenes with advanced lighting and shadowing techniques. Other developers also began to tap into the power of GPUs to dramatically accelerate additional workloads in high performance computing (HPC), deep learning, and more.

Data Analytics uses a range of different technologies for effective solutions, including:

  • Predictive Analytics uses statistical modeling to help determine potential outcomes and future performance, based on both legacy data and the current flow of your company’s data. By being able to identify patterns in data that are likely to emerge again, businesses can determine where’s best to focus resources, ensuring a better plan for the future. These technologies typically use statistical algorithms and Machine Learning.
  • Machine Learning is a subset of AI which uses algorithms that learn on their own. ML capabilities can ingest & analyse data to predict outcomes, without specified programming.
  • Data Mining enables users to sift through enormous datasets and understand what’s relevant and what the relationships are between data points. Today’s data mining technologies allow you to carry out these tasks at exceptional speed.

Why use a GPU Database for Analytics?

  • To empower your users to analyse more data, faster, and with ease.
  • You want decision support and business critical insights.
  • The ability to interactively query, visualise, and power data science workflows over billions of records with a wide range of accelerated analytics solutions.

If you’re part of an organisation that wants to get the most out of your rapidly growing datasets, having a GPU-powered database is certainly a great route to go.

Once a business has well organised data at their fingertips, many of their challenges can be solved by applying the appropriate analytics process.

Movements in the GPU database market

Over the past few years, the cloud-based GPU revolution has completely reshaped IT architecture, with the ability for computing resources to automatically scale based on immediate requirements. Over the next few years, the vast majority of organisations are expected to have (or be moving to) cloud-based systems to meet their data, software, and infrastructure needs.

The monumental rate of progress found in the GPU database market isn’t looking to slow down at any point soon, as it’s closely linked to the constantly evolving technology on which it is powered – as is the commercial advantage found by those who are using them.

A smarter integration

Instead of overhauling existing systems, our platform can be easily integrated into most business environments. Brytlyt is the future-proofed approach to data processing and business analytics.

Tomorrow’s technology, today

Plus, its adaptable functionality means you can continue to develop the platform as your needs change.

To learn more about how Brytlyt can help your organisation boost productivity and save costs with GPU Databases, you can get in touch here.