Match each Google Cloud enterprise workload requirement on the left with the database or persistent block storage service on the right that best satisfies the technical constraints with minimal operational overhead.
- A high-throughput, low-latency NoSQL data store requiring single-digit millisecond latency for real-time time-series IoT ingestion at petabyte scale.Cloud Bigtable
- A globally distributed transactional relational database requiring full ACID compliance, horizontal scaling across multi-region deployments, and up to 99.999% availability.Cloud Spanner
- An ephemeral, ultra-high IOPS storage volume providing sub-millisecond latency attached physically to the hypervisor host for temporary processing and scratch space.Local SSD
- A fully managed regional relational database engine (MySQL, PostgreSQL, or SQL Server) supporting standard OLTP applications with automated backups and cross-zone High Availability (HA).Cloud SQL
Cevap
High-throughput petabyte IoT time-series maps to Cloud Bigtable. Globally distributed ACID relational database maps to Cloud Spanner. Ephemeral ultra-high IOPS sub-millisecond scratch space maps to Local SSD. Managed regional MySQL/PostgreSQL with HA maps to Cloud SQL.
Each requirement directly aligns with GCP's database and storage classification guidelines: Cloud Bigtable for high-throughput NoSQL time-series; Cloud Spanner for globally scalable ACID relational data; Local SSD for non-persistent, physically attached high-IOPS scratch disks; and Cloud SQL for standard managed regional relational databases.
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Anahtar Kavram
Matching workload storage and relational requirements to appropriate Google Cloud database engines and persistent disk options.
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