One of the most effective ways to improve performance and minimize cost in database systems today is by avoiding unnecessary work, such as data reads from the storage layer (e.g., disks, remote storage), transfers over the network, or even data materialization during query execution. Since its early days, Apache Hive improves distributed query execution by pushing down column filter predicates to storage handlers like HBase or columnar data format readers such as Apache ORC.

The global pandemic continues to impact our world in so many ways. But it has also served as a catalyst for technological change—a forcing function that is accelerating cloud migration. Every company wants to create better products or services, differentiate offerings, price strategically, grab more market share, retain customers, and grow in a sustainable manner.

We don’t even need a moment to gather which operating system is the most used one. Android development is a booming business because of the number of users it has. It is open source and its development can be ported across devices with relative ease. Plus, it has good backwards compatibility across versions. And, precisely due to this diversity, the need for testing on many devices is paramount.