A logistics enterprise is designing a high-throughput fleet tracking platform on Google Cloud to record continuous telemetry and diagnostic metrics from active delivery vehicles. The ingest layer requires consistent sub-10 millisecond write latencies, must dynamically scale capacity up to hundreds of terabytes without database schema maintenance or manual sharding, and relies solely on single-row key lookups by vehicle ID and timestamp. Which database architecture should you recommend to meet these requirements with minimal operational overhead?
- Provision Cloud Bigtable instances using SSD storage for high-throughput time-series key-value telemetry data.Cevap
- BDeploy a Cloud SQL for PostgreSQL instance configured with regional High Availability and standard persistent disks (pd-standard).
- CDeploy Compute Engine instances running on Spot VMs attached to Local SSD scratch disks hosting a self-managed NoSQL cluster.
- DStream incoming vehicle telemetry files directly into Cloud Storage buckets configured with the Archive storage class.
Cevap
Provision Cloud Bigtable instances using SSD storage for high-throughput time-series key-value telemetry data.
Cloud Bigtable is a fully managed NoSQL wide-column database optimized for high-volume time-series metrics and telemetry data. It offers sub-10 millisecond latency and scales seamlessly to petabytes of key-value data with low operational overhead.
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Cloud Bigtable is the optimal GCP database choice for high-throughput, low-latency NoSQL time-series data at multi-terabyte scale.