Google Cloud Digital LeaderData and AI with Google CloudHard
A logistics company wants to optimize delivery routes by predicting traffic congestion and delivery times. They plan to use historical GPS data, weather forecasts, and real-time traffic information. They need a flexible, scalable database that can handle large volumes of rapidly changing semi-structured data (like sensor readings and traffic updates) and provide low-latency access for their route optimization engine. Which Google Cloud database is best suited for this scenario?
- ACloud SQL
- BFirestore
- CBigQuery
- DCloud Spanner
Show answer & explanationAnswer & explanation
Correct answer: B. Firestore
Firestore is a NoSQL document database designed for flexible, scalable storage of semi-structured data and low-latency access, making it ideal for managing rapidly changing data like real-time traffic and sensor readings for route optimization.
Why the other options are wrong
- A. Cloud SQL is a relational database, not ideal for rapidly changing, semi-structured data and global scale with low-latency access.
- C. BigQuery is a data warehouse for analytics, not an operational database for low-latency retrieval of rapidly changing individual data points.
- D. Cloud Spanner is a globally distributed relational database, offering strong consistency, but Firestore is better for flexible, semi-structured data with low-latency access at scale.
Firestore
A flexible, scalable NoSQL document database for mobile, web, and server development, offering real-time synchronization and offline support.
- NoSQL document model, highly flexible schema
- Scales globally and provides low-latency access
- Real-time updates and offline capabilities
Memory trick: Fire-fast storage for flexible, ever-changing data.