Honeycomb strives to be a fast, efficient tool; our storage back-end satisfies the median customer query in 250ms (and the P90 in 1.3 seconds). Still, every system has its limits, and customers with large datasets know that querying over a long time range, grouping by high-cardinality columns, building complex derived columns, and throwing a quantile or heat map into the mix can lead to some pretty slow queries. If this sounds familiar: good news!
You've got this month’s salary, and now it is time for shopping! You’re surfing in the Amazon, here are the earphones that you wanted to buy for a long time. You added it to cart. What a coincidence! There is a discount option with a coupon for this product. This must have made you happy as everyone loves discounts!