Google Cloud Spanner vs MySQL

Scale and architecture

MySQL is a single-primary relational database that scales vertically and through read replicas; scaling writes beyond one node requires application-level sharding or tools such as Vitess, which adds operational complexity. For the large majority of workloads that fit comfortably on one well-sized instance, this is a non-issue and MySQL performs well.

Spanner is architected to scale horizontally by design, automatically distributing and resharding data across nodes and regions while presenting a single relational database. It removes the sharding burden, which is its core reason to exist: relational semantics at a scale where a single-primary engine would require extensive custom partitioning.

Consistency and availability

Spanner offers strong external consistency across regions using the TrueTime clock system, delivering linearizable transactions globally with high availability backed by a service-level agreement up to 99.999 percent for multi-region instances. MySQL provides ACID transactions on its primary node, and replica reads are typically asynchronous and eventually consistent, so cross-region strong consistency requires careful design. For globally consistent writes, Spanner is the more direct fit.

Ecosystem and maturity

MySQL is one of the most widely deployed databases in the world, with decades of tooling, hosting options, documentation, and talent availability. It runs everywhere, from a laptop to managed services on every major cloud, and integrates with virtually every framework. Spanner is a younger, proprietary service with a smaller ecosystem and talent pool, though it is well-documented within Google Cloud and supports a PostgreSQL-dialect interface to ease adoption.

Pricing and cost

MySQL is free and open source; cost comes from hosting (self-managed infrastructure or managed services such as Cloud SQL, Amazon RDS, or Aurora) and optional commercial support or Oracle's MySQL Enterprise Edition. For small and mid-sized workloads it is inexpensive. Pricing verified June 2026.

Spanner bills for compute capacity in processing units (1,000 PU equals one node) plus storage, with granular instances available below one node and committed-use discounts of 20 percent for one year or 40 percent for three years. Production deployments commonly run from several hundred to a few thousand dollars per month and scale up with redundancy. Spanner has a higher cost floor than a small MySQL instance, and is exclusive to Google Cloud.

What buyers say

Buyers frequently note that MySQL is dependable, inexpensive, and supported by an enormous ecosystem, making it the default for web and business applications where its scale ceiling is rarely reached. The recurring MySQL criticism is that scaling writes globally requires sharding or additional tooling and operational effort. Spanner buyers frequently praise the elimination of sharding, its strong global consistency, and high availability for transactional systems that genuinely need multi-region scale. The common Spanner complaints are cost, particularly the floor for smaller workloads, and lock-in to Google Cloud along with a smaller talent pool. Across both, experienced architects advise matching the tool to scale: MySQL for the many workloads that fit a single primary, and Spanner reserved for systems whose write volume or global consistency requirements outgrow a traditional relational engine.

When to choose Google Cloud Spanner

Choose Google Cloud Spanner when your workload genuinely needs horizontal write scale and strong consistency across regions that a single-primary relational engine cannot deliver without heavy sharding. It fits global financial systems, large-scale inventory, gaming, and multi-region transactional platforms already on Google Cloud. Accept the higher cost floor and single-cloud lock-in as the trade for managed global consistency, and use the PostgreSQL-dialect interface and committed-use discounts to ease adoption and control spend.

When to choose MySQL

Choose MySQL for the large majority of web and business applications that fit on a managed or self-hosted instance, where maturity, ubiquitous tooling, low cost, and abundant talent are decisive. It is the pragmatic default unless you have a concrete, near-term need for automatic global scale. Use read replicas for read scaling and a managed service such as Cloud SQL, RDS, or Aurora to reduce operations, and revisit distributed options only when write scaling becomes a real constraint.

Alternatives to both