In this module, we will cover storage and database services in Google Cloud. Every application needs to store data, whether it's business data, media to be streamed, or sensor data from devices. From an application centered perspective, the technology stores and retrieves the data. Whether it's a database or an object store, is less important than whether that service supports the application's requirement for effectively storing and retrieving the data given its characteristics. Google offers several data storage services to choose from. In this Module, we will cover Cloud Storage, Filestore, Cloud SQL, Cloud Spanner, Cloud Firestore, and Cloud Bigtable. Let me start by giving you a high level overview of each of these services. This table shows the storage and database services, and highlights the storage service type, object, file, relational, non-relational, or data warehouse, what each service is good for and intended use. BigQuery is also listed on the right. I'm mentioning the service because it sits on the edge between data storage and data processing. You can store data in BigQuery, but the intended use for BigQuery is big data analysis and interactive querying. For this reason, BigQuery is covered later in the course. If tables aren't your preference, I've also added to this decision tree to help you identify the solution that best fits your application. Let's walk through this together. First, ask yourself, is your data structured? If it's not, then ask yourself, do you need a shared file system? If you do, choose Filestore. If you don't, then choose Cloud Storage. If your data is structured, does your workload focus on analytics? If it does, you will want to choose Cloud Bigtable or BigQuery, depending on your latency and update needs. Otherwise, check whether your data is relational. If it's not relational, then choose Cloud Firestore. If it is relational, you'll want to choose Cloud SQL or Cloud Spanner depending on your need for horizontal scalability. Depending on your application, you might want to use one or several of these services to get the job done. For more information on how to choose between these different services, see the link section in this video. Before we dive into each of the data storage services, let's define the scope of this module. The purpose of this module is to explain which services are available, and when to consider using them from an infrastructure perspective. I want you to be able to setup and connect to a service without detailed knowledge of how to use a database system. If you want a deeper dive into design, organizations, structures, schemas, and details on how data can be optimized, served, and stored properly within each of these different services, I recommend Google Cloud's Data Engineering courses. Let's look at the agenda. This module covers all of the services that we've mentioned so far. To become more comfortable with these services, you'll apply them in two labs. I'll also provide a quick overview of Cloud Memorystore, which is Google Cloud's fully managed Redis service. Let's get started by diving into Cloud Storage and Filestore.