We are thrilled to announce that Google has been named a Leader in The Forrester Wave™: Cloud Data Warehouse, Q1 2021 report. For more than a decade, BigQuery, our petabyte-scale cloud data warehouse, has been in a class of its own. We're excited to share this recognition and we want to thank our strong community of customers and partners for voicing their opinion. We believe this report validates the alignment of our strategy with our customers’ analytics needs.
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.
Have you heard of the misconception that agile is about velocity: i.e. delivering more, at a faster rate? Although this statement is true, it is ultimately meaningless if you don’t deliver value and the customer is not satisfied.
Whether you're breaking up a monolith or building a green-field application, you may consider using a microservice architecture. Like all app architectures, this model brings opportunities and challenges that a developer must be aware of in order to make the most of this app design. One such challenge is ensuring communication between your microservices.
In today’s post, we’ll dive into how we, at AppSignal, solved a daunting engineering challenge. Giving you a look into the kitchen, this post will show you how we tested a new database in production without having to worry about errors/downtime. Alright, let’s get cooking!