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Cloud · GCP in Depth

Bigtable vs BigQuery vs Spanner vs Cloud SQL

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gcpbigquerybigtablespannercloud-sql

Question

How do you choose between Bigtable, BigQuery, Spanner and Cloud SQL?

Solution

Choose BigQuery for large-scale analytical scans and aggregations over columnar datasets, and choose Bigtable for high-throughput, low-latency key-value lookups on wide-column NoSQL tables. Select Cloud Spanner when your system requires horizontally scalable relational tables with global ACID transactions, and pick Cloud SQL for standard regional transactional databases running PostgreSQL or MySQL. The choice depends on query access patterns, required read and write latencies, and transaction boundaries.

Matching database engines to query patterns

Cloud databases are specialized tools designed around specific operational workloads. Evaluating read and write paths prevents costly architectural mismatches.

Analytical Aggregations  ---> BigQuery   (Columnar warehouse, TB/PB scans)
Low-Latency Key Lookups   ---> Bigtable   (Wide-column NoSQL, sub-10ms writes)
Global ACID Transactions  ---> Spanner    (Distributed SQL, multi-region)
Regional Relational Apps  ---> Cloud SQL  (Managed Postgres/MySQL OLTP)

Each service fulfills a specific operational niche across modern platforms:

  • BigQuery is a serverless data warehouse optimized for scanning millions of rows to compute analytical aggregations, window functions, and business intelligence reports. It is inefficient for frequent single-row lookups or point updates.
  • Cloud Bigtable handles millions of read and write operations per second with single-digit millisecond latency. It excels at time-series metrics, IoT telemetry feeds, and user fraud counters accessed via row keys.
  • Cloud Spanner combines relational schemas, SQL querying, and foreign keys with global scale and external consistency using TrueTime synchronization. It powers global financial ledgers and multi-continent inventory systems.
  • Cloud SQL offers familiar managed relational databases for regional transactional applications with moderate connection volumes and simple relational schemas.

Decision matrix for data architects

Evaluate storage engines against these workload characteristics:

  • If queries run OLAP scans across gigabytes to terabytes with SQL, choose BigQuery.
  • If writes exceed tens of thousands of records per second and reads fetch specific row keys, choose Bigtable.
  • If the application demands relational integrity across multiple geographies with zero downtime maintenance, choose Spanner.
  • If standard relational features fit on a single primary instance with read replicas, choose Cloud SQL.
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