Data growth rates are continuing to explode, especially as companies look to capitalize on data-related trends such as IoT, machine learning, AI, and advanced analytics. While all of this has contributed to extreme spikes in all types of data, it has dramatically increased the volume of unstructured data in particular.
Unstructured data is now the most common type of data because it really could be any type of information such as text data, sensor data, video, analytics, and more. As the name suggests, unstructured data is not stored in a typical database format, such as a relational database management system (RDBMS).
Unfortunately, traditional data storage techniques simply weren’t designed to be able to scale to keep pace with such aggressive growth rates. Any company would be hard pressed to add the servers, file systems, and other required components to attempt to scale unstructured datasets using traditional methods. This makes internal processes difficult to manage – and inevitably impossible – and will certainly lead to performance degradation in the future.
Yet turning to public cloud vendors may not always be the best option either. On one hand, hyperscalers can definitely provide the storage just about any company needs for its unstructured data, but most contracts charge fees related to managing data, most notably when it comes to API calls and data egress. While these fees are generally estimated at mere fractions of a penny, they may seem innocent in the beginning. But depending on a company’s strategies and use of data, these charges can quickly add up and lead to high costs that catch everyone off guard.
It’s a real challenge. As companies attempt to collect and store high – and constantly growing – volumes of data, many struggle to find the best approach, one that balances cost, data availability/management, and support for specific business strategies such as geographic diversity, latency, and more.
All of these trends – and related challenges – led to the natural evolution and introduction of object storage. Object storage is a more effective way to deliver simplicity and scalability related to unstructured data, and now DataBank is offering our own Object Storage solution for companies looking for this same simplicity and scalability, all in a much more cost-effective pricing model.
The DataBank Object Storage solution was designed with all of these considerations in mind. We bundle everything our customers need with one, easy-to-understand price based on each terabyte of storage. We don’t charge for data egress or API calls, an important step in making IT expenses much more affordable and predictable – and eliminating fee surprises later.
Our object storage model is also designed to further reduce complexity by using the industry-standard Amazon S3 API protocol. DataBank customers can move their data to our Object Storage sites from the cloud, their existing data center, or wherever it resides now and enables effective storage and easy retrieval of any amount of data from anywhere.
With the DataBank Object Storage solution, companies can have their cake and eat it, too. In this case, it means they can store their data wherever they like, enjoy scalability and full control, and even eliminate the potential for surprisingly high data egress fees. To learn more, please visit www.databank.com today.
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