Semi-structured data storage
1. Semi-structured data storage
Semi-structured data contains elements of both structured and unstructured data. It does have some defining or consistent characteristics, but generally doesn’t follow a structure as rigid as a relational database. Semi-structured data is easier to organize because it usually contains some organizational properties, such as tags or metadata. An example of semi-structured data is an email message. While the actual content of the email is unstructured, it does contain structured data such as the name and email address of the sender and recipient, the time sent, and so on. Google Cloud offers two semi-structured data storage products, Firestore and Bigtable. Firestore is a flexible, horizontally scalable, NoSQL cloud database for storing and syncing data in real-time. Firestore can be directly accessed by mobile and web applications. Firestore performs data storage in the form of documents, with the documents being stored in collections. Documents support a wide variety of data types, such as nested objects, numbers, and strings. One of Firestore’s main features is automatic scaling. It’s been designed to scale automatically depending on user demand, but retains the same level of performance irrespective of database size. Firestore also provides offline usage through a comprehensive database on users’ devices. Offline data access ensures that applications run without interruption, even if the user gets disconnected from the internet. And then there’s Bigtable, Google's NoSQL big data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. Bigtable is designed to handle large workloads at consistent low latency, which means Bigtable responds to requests quickly, and high throughput, which means it can send and receive large amounts of data. For this reason, it's a great choice for both operational and analytical applications, including Internet of Things, user analytics, and financial data analysis. When deciding on a storage option, you might choose Bigtable if you’re working with more than 1 TB of semi-structured or structured data, data is fast with high throughput, or it’s rapidly changing, you’re working with NoSQL data, data is a time-series or has natural ordering, you’re working with big data and running batch or real-time processing on the data, or you’re running machine learning algorithms on the data.2. Let's practice!
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