When choosing your data warehouse, one of the key decisions will be that of scalability; the ability of your data warehouse to meet your needs for data storage today and for the future. If we take it as a given that the functionality and capabilities of data warehouses are under ever-increasing demands from businesses now, then the ability to meet the scaling requirements for the future is critical for any business.
This is only compounded by the ever-quickening digital march forwards, with the sheer growth in the volume of data, alongside the additional data points that technologies such as IoT, AI, 5G connectivity bring.
Amazon Redshift has clearly been designed with huge scale in mind. Firstly, and crucially, it is built in the AWS Cloud, therefore the historic problem of having to firstly buy and then maintain specialist hardware for a business’s data warehousing requirements do not exist here. Also, with historical on-premise solutions, additional hardware would need to be purchased to keep up with the demanding data requirements of any business looking to exploit its growing data assets.
One of the biggest benefits of having Redshift within the AWS Cloud is that it provides a flexible architecture that can scale in seconds to meet changing storage demands. A major issue facing organizations with rapidly changing data requirements is that scaling can be both costly and complex.
Thanks to AWS, Redshift can be scaled up or down by quickly activating individual nodes of varying sizes. This scalability also means cost savings, as companies aren’t forced to spend money maintaining servers that are unused or to quickly purchase expensive server space when the need arises. This is especially useful for smaller companies which experience significant growth in a short period of time and must scale their existing solutions accordingly.
Boosted performance with Brytlyt’s accelerated GPU processing
Redshift developers have put a lot of work into ensuring optimal performance of the core Redshift engine. By using capabilities such as columnar storage and MPP processing, Redshift has performance capabilities that enable it to have a competitive offering. However, the issues that plague large datasets remain present with Redshift and by installing Brytlyt’s accelerated GPU database to complement your analytics infrastructure, the full power of the vast volumes of data can be fully unleashed.
By integrating Brytlyt into your Redshift environment, a very straight forward task that can be completed within the day, then Redshift users can:
- Overcome restricted concurrent user loads, meaning users don’t have to wait to be served in queueing systems
- Spend less resource on building complex data pipelines and pipeline maintenance
- Increase query responsiveness and flexibility
- Perform greater, more in-depth data exploration on larger datasets
- Avoid having to limit the scope of data analyses to overcome common performance challenges
Get in touch to learn about how Brytlyt’s GPU database can accelerate your Redshift solution or fill out the form below to request a free trial for your business.