Data gravity: what is it, and what can you do about it?

As volumes of data grow, so too does the force they exert on the wider IT environment, pulling applications into closer proximity. This is data gravity – our blog explores how businesses can work around it or leverage it to their advantage.

Any object that has mass exerts a gravitational pull on the objects around it, the strength of this force increasing with the mass of the object. As business data stores, particularly in the cloud grow ever larger, a similar force is developing in the digital world – data gravity. 

Much like actual gravity, data gravity is a powerful force that is increasingly influencing data management strategy and can have outsized impacts on costs and other critical outcomes. When properly considered, it helps speed up business processes and drive cost efficiency, but left unchecked, organisations may end up with bigger bills and fewer application and data management options. 

Understanding data gravity 

The term data gravity was first coined in 2010. It describes a phenomenon where large pools of data attract applications into their environment, creating even more data in the process. The underlying mechanics are straightforward – many business applications require readily available data to function as intended, and hosting those applications in the same environment as existing data storage reduces latency and increases the throughput of those applications. 

In turn, applications produce their own data, and this data enters the storage environment, making it even larger and pulling more applications into the same environment. Just like actual gravity, data gravity can easily become a recurring loop as more mass (or data) is pulled closer to the centre of gravity. 

While there are applications that can benefit from the pull of data gravity, it can result in bigger challenges for the organisation if not properly factored into a data management strategy. The environment needs to be able to scale to allow for new data being generated and applications moving closer to the centre of data gravity. 

Data gravity in the cloud 

The obvious answer when dealing with data gravity is to better harness the cloud to take advantage of rapid scaling infrastructures, especially data storage. This provides organisations with an easy way to continue to grow large data stores without needing to worry about capacity, physical space or upkeep costs. But the way many public cloud environments are set up can amplify the pull of data gravity and exacerbate the challenges it can bring. 

Since many public clouds charge egress fees, it can be cost-prohibitive for organisations to transfer large volumes of data. Beyond this, the scale of data storage that businesses may use in the cloud makes it difficult, if not impossible, to transfer the data to an on-premises infrastructure. 

This adds to the data gravity spiral, as data and applications can easily be migrated to the cloud but moving them out comes with significant cost. This is known as artificial data gravity, caused less by the data itself and more by the structure of public clouds. 

Both artificial and natural data gravity have a significant impact on repatriation strategies, but it can be harnessed to support them, not hinder them. If large volumes of data storage are left in the cloud while some applications are repatriated, IT teams have to work against the forces of data gravity.  

But, by understanding data gravity, this can be reversed. Repatriating data and applications from the cloud means that data gravity helps pull the rest of the environment to the new infrastructure, whether its on-prem, or just a different cloud. 

Get ahead of your data with FluidOne 

At FluidOne, our Data and Automation function leads in technical innovation, with a portfolio of advanced solutions geared to helping you get the most from your data environment. That means we come to the table with an in-depth understanding of the mechanics behind data gravity – and how to help you harness it to your advantage, no matter what your environment looks like.  

Our AI & machine learning models help analyse your current data management strategy and identify areas for improvement, highlighting opportunities to optimise your data storage without being held back by data gravity. 

These can be combined with powerful data visualisation and business intelligence tools give you the ability to easily understand where data storage is consolidating, pulling the rest of your environment closer in turn. Having this information to hand helps drive data-driven decision making, and a more informed data management strategy. 

Since this level of management can be time-consuming, it's also something we factor into our managed Enterprise IT services, helping deliver a data management strategy that’s right for your business, while internal IT resource is free to focus on other projects. 

What's next? 

Whether you’re planning a move into the cloud, away from it, or just between different environments, understanding the full scope of your data is critical. Our cloud readiness and optimisation assessments can give the insight your business needs to devise an informed strategy that takes centres of data gravity into account.

Take a look at our cloud readiness infographic or speak to the team at FluidOne about our free cloud assessments which cover both cloud readiness and cloud optimisation.