In our previous posts, we talked about how Data Warehouses and Data Lakes can help us manage our data in a more secure, cost-effective, reliable, and scalable way. But there is another critical concept we need to understand in order to work with these architectures: Data Pipelines.
Nearly every business is facing new challenges in how to store and effectively utilize data. Today we'll look at how data lakes solve these challenges and why GCP is the available, scalable, cost-efficient data lake hosting solution your business needs.
The concept of Data Warehouses (DWs) has been around since the late 80s, and it is still a critical component for any company that wants to adopt a data-driven culture. Here's why Google Cloud Platform's BigQuery might be the right choice to host your data warehouse.
Although Quarkus is relatively new, it's attracting a lot of attention. The project was created by the open source community and consists of a Kubernetes-native Java stack tailored for OpenJDK Hotspot and GraalVM, crafted from the best-of-breed Java libraries and standards. Hence, it's an excellent option for new cloud native technologies like serverless and microservices.
Cloud computing is one of the main investments of Amazon, Microsoft, and Google, which directly compete against each other with their respective AWS, Azure, and GCP cloud providers. With a fierce competition for the market share of the infrastructure of several enterprise organizations, each provider has adapted differently to the needs of customers to offer services that optimize businesses.
Enterprise organizations around the world have been forced to transform themselves digitally to maintain business operations. Resilient infrastructure is key to scaling and keeping operations running, but how can your business grow sustainably without getting lost in IT spending?