Google Cloud Digital LeaderGeneral knowledge of Google CloudHard
A cybersecurity firm is building a new threat intelligence platform on Google Cloud. They need to store massive amounts of security log data (terabytes per day) for real-time analysis and historical lookups. The data is high-throughput, low-latency for reads and writes, and key-value structured, with strong consistency requirements. Which Google Cloud NoSQL database is best suited for this extreme scale and specific data model?
- ACloud Spanner
- BFirestore
- CMemorystore
- DCloud Bigtable
Show answer & explanationAnswer & explanation
Correct answer: D. Cloud Bigtable
Cloud Bigtable is a fully managed, petabyte-scale, NoSQL wide-column database service ideal for analytical and operational workloads, including large-scale time-series data like security logs. It offers high throughput and low latency for both reads and writes, fitting the 'extreme scale' and 'high-throughput, low-latency' requirements for key-value structured data.
Why the other options are wrong
- A. Cloud Spanner is a globally distributed relational database, not a NoSQL key-value store for log data.
- B. Firestore is a NoSQL document database, better for mobile/web apps, not typically petabyte-scale high-throughput log data.
- C. Memorystore is an in-memory data store (Redis/Memcached) for caching, not persistent petabyte-scale storage for logs.
Google Cloud Bigtable
Cloud Bigtable is a fully managed, petabyte-scale NoSQL wide-column database for large analytical and operational workloads, like IoT and time-series data.
- Ideal for high-throughput, low-latency read/write operations.
- Supports massive datasets (petabytes) and millions of requests per second.
- Commonly used for IoT, analytics, and personalization.
Memory trick: NoSQL in GCP: Firestore for Documents, Bigtable for Wide-Column, Memorystore for Cache.