DynamoDB vs Google Cloud Spanner

DynamoDB and Google Cloud Spanner both scale horizontally across a distributed cluster, but they make opposite core bets. DynamoDB is a serverless AWS NoSQL key-value and document store designed around known access patterns. Spanner is a globally-distributed relational database that keeps full SQL and strong (externally consistent) transactions even across regions, using Google's TrueTime clock.

Should you use DynamoDB or Spanner?

Choose DynamoDB if you are on AWS and want a serverless NoSQL store with pay-per-request billing and predictable latency for key-based access. Choose Google Cloud Spanner if you need relational SQL, joins, and strong transactional consistency at global scale — a horizontally scalable database that still behaves like a relational one. Relational guarantees at scale versus serverless NoSQL simplicity is the deciding axis.

DynamoDB vs Spanner at a glance

CharacteristicDynamoDBGoogle Cloud Spanner
Data modelNoSQL key-value and document; flexible per-item schema, items up to 400 KBRelational — tables, rows, columns, and schemas (also exposes graph, key-value, and search capabilities)
Query languageNative API (GetItem, Query, Scan) plus PartiQL, a SQL-compatible languageFull SQL in two dialects — GoogleSQL and a PostgreSQL-compatible dialect
Joins & relationsNo JOIN operator; AWS recommends denormalizing around access patternsFull relational joins, foreign keys, and interleaved tables
ConsistencyEventually consistent by default; strongly consistent reads per request (within a Region)External (strong) consistency by default, including across regions, backed by the TrueTime clock
TransactionsACID transactions across multiple items within a RegionGlobally-consistent ACID transactions, including across regions
Scaling modelAutomatic partitioning; serverless on-demand or provisioned capacityHorizontal scaling via provisioned compute (nodes / processing units) with autoscaling; storage scales separately
Multi-regionGlobal Tables — multi-Region, active-active replication (eventually consistent between Regions)Multi-region configurations that preserve strong consistency across regions
Pricing / ops modelPay-per-request (on-demand) or provisioned capacity plus storage; serverless, AWS-onlyProvisioned compute capacity plus storage (and network); node/processing-unit-based, GCP-only
Best-fit workloadsHigh-scale operational apps with known key access needing consistent low latencyGlobal relational systems needing strong consistency, SQL, and joins at scale

When DynamoDB is the better choice

  • You are on AWS and want serverless NoSQL. On-demand capacity has nothing to provision, scales to traffic, and scales to zero when idle.
  • Your access patterns are known and key-based. DynamoDB's partition/sort-key model gives consistent single-digit-millisecond latency when keys are designed around your reads.
  • You do not need relational joins or global strong consistency. If a denormalized, key-oriented model fits, you avoid paying for guarantees you will not use.
  • You want native AWS integration with IAM, Lambda, and Streams.

When Spanner is the better choice

  • You need relational SQL at global scale. Spanner keeps joins, schemas, and full SQL while scaling horizontally — you do not give up relational semantics to scale out.
  • You need strong consistency across regions. TrueTime-backed external consistency lets multi-region transactions behave as if serialized, which DynamoDB's Global Tables (eventually consistent between Regions) do not provide.
  • Your workload is relational and query-flexible. Ad-hoc joins and evolving queries across normalized tables fit Spanner's model.
  • You are on GCP and want its managed global database with high-availability SLAs.

Working with DynamoDB

If DynamoDB fits, DynoTable is a native desktop client for it on macOS, Windows, and Linux. It reads your standard AWS credential chain, so your data stays in DynamoDB with nothing to migrate. For teams used to Spanner's SQL, its SQL Workbench expresses relational-shaped queries — joins, GROUP BY, aggregates — within DynamoDB's access-pattern rules by compiling them to DynamoDB's Query/Scan, and its AI assistant runs on your own AWS Bedrock credentials.

The SQL for DynamoDB and PartiQL vs SQL guides explain what carries across from SQL, and the free DynamoDB Expression Builder generates key conditions, filters, and update expressions in SDK, CLI, and PartiQL form. DynoTable is a closed-source commercial app; this page describes what it does, not how it is built.

FAQ

Is Spanner a NoSQL database like DynamoDB?

No. Spanner is a relational database with full SQL, joins, and schemas that happens to scale horizontally like a distributed system. DynamoDB is a NoSQL key-value and document store with no JOIN operator. Spanner's distinguishing claim is keeping relational, strongly-consistent semantics at global scale.

Does DynamoDB offer global strong consistency like Spanner?

Not in the same way. DynamoDB provides strongly consistent reads within a single Region, and Global Tables replicate across Regions but with eventual consistency between them. Spanner uses TrueTime to provide external (strong) consistency for transactions even across regions.

Can DynamoDB replace Spanner?

Only when you do not need relational SQL or global strong consistency. If your access is key-based and a denormalized model fits, DynamoDB is simpler and serverless. If you rely on joins, ad-hoc SQL, or strongly-consistent cross-region transactions, those are Spanner's purpose — replacing it means remodeling your data around DynamoDB's keys and giving up those guarantees.

Last verified 2026-07-12 against the official AWS DynamoDB Developer Guide and Google Cloud Spanner documentation. Google Cloud Spanner is a trademark of Google LLC; referenced here for identification only.

Work with DynamoDB without the Console

DynoTable is a fast desktop client for DynamoDB — browse tables, run SQL-style queries, and edit items locally.