High Volume Demand occurs at any given moment, your website can get a huge wave of traffic and customers. If you have a robust data architecture in place, it will guarantee that that moment will be a cause for a celebration and not a concern.
This year’s holiday season is supposed to be one of the busiest on record. The ease of shopping on smartphones has created a brand-new, demanding audience, who wants companies to be able to handle or process holiday traffic promptly.
What do your company and database need to be prepared for this holiday season? What are the hidden challenges your database need to be ready to face?
Conversion rates are usually unaffected as your database fetches data and serves it to an added number of users. However, during the holidays, people are looking to buy. Along with a High Volume Demand of 100-300%, you may see an increase in conversions from 3% to 7.5%, an increase in 250% on higher volume.
A write or an update to your database can cost you four times as much as a read. Make planning for increased traffic an essential part of the plan. To keep performance optimal, take into account that writes impact every future query, often invalidating much of your cached info.
If your marketing plan and your coupons are a hit, your business will have thousands of satisfied shoppers buying at the same time. If you manage your concurrency issues, there is nothing to write home about.
The real issue is that you have targeted concurrency. You may offer a 10% discount on a specific item, which places High Volume Demand on one area of your database. Don’t forget that 1 in 4 shopping carts are abandoned due to performance issues.
3. High Availability
If $40,000 is billed every second on Cyber Monday, the costs of your database stalling can be critical. What happens if you get overloaded? What could happen if your server goes down?
The effects of a database failure, even if just for a minute, are enormous. If big retail companies such as Target can’t handle their traffic, how can you do it?
Be a step ahead of even the largest enterprises using a relational solution with a distributed database that replicates in real time and has high-availability.
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