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Databases · head to head

Azure SQL vs DynamoDB

Azure SQL logo

Azure SQL

Databases

Intelligent, scalable cloud database service from Microsoft

From
Free
Rated
-
Full reviewWebsite
DynamoDB logo

DynamoDB

Databases

AWS-only managed key-value and document database with fixed per-partition throughput limits and no ad hoc queries.

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Azure SQL ecosystem lock-in limits flexibility compared to open-source or multi-cloud solutions; DynamoDB access patterns must be designed into the key schema before launch; a query nobody anticipated needs a new global secondary index, which is a full extra copy of the projected attributes billed as storage and as writes, or an offline migration.
  • They diverge on capability: Azure SQL covers Intelligent Performance, DynamoDB covers Managed and serverless.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Azure SQL and DynamoDB actually diverge.

Attributes where Azure SQL and DynamoDB differ
AttributeAzure SQLDynamoDB
Pricing modelUnknownusage-based
PlatformsCloud (Microsoft Azure)AWS
Founded19752006

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Azure SQL

  • Intelligent Performance
  • Advanced Security
  • Hyperscale
  • Serverless Compute
  • Geo-replication
  • Automatic Tuning
  • Built-in AI
  • Power BI

Only in DynamoDB

  • Managed and serverless
  • Predictable latency
  • On-demand or provisioned capacity
  • Global secondary indexes
  • Transactions
  • DynamoDB Streams
  • Global tables
  • Point-in-time recovery

What people use each for

The jobs each tool is most often brought in to do.

Azure SQL

  • Transaction processingnot DynamoDB
  • Data storagenot DynamoDB
  • Application backendnot DynamoDB
  • Reportingnot DynamoDB
  • Data analyticsnot DynamoDB

DynamoDB

  • High-volume keyed workloads such as sessions, shopping carts, device state or user profiles where the access pattern is fixed and knownnot Azure SQL
  • Traffic that spikes unpredictably, where on-demand capacity absorbs a burst without a capacity-planning exercisenot Azure SQL
  • Serverless applications on Lambda, where an HTTP-based datastore avoids the connection pooling problem relational databases havenot Azure SQL
  • Event or telemetry ingestion where writes vastly outnumber reads and each record is retrieved by a known identifiernot Azure SQL

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Azure SQL

  • Ecosystem lock-in limits flexibility compared to open-source or multi-cloud solutions
  • Managed service reduces control over database configuration and optimization tuning
  • Pricing complexity with consumption-based model can be unpredictable at scale
  • Less operational depth compared to Amazon RDS for advanced scaling scenarios
  • Azure PostgreSQL is less compelling than dedicated PostgreSQL providers outside Azure ecosystem

DynamoDB

  • Access patterns must be designed into the key schema before launch; a query nobody anticipated needs a new global secondary index, which is a full extra copy of the projected attributes billed as storage and as writes, or an offline migration.
  • Global secondary indexes are eventually consistent and cannot be read strongly, so a read-after-write against an index can legitimately miss the item that was just written, and application code must be written to tolerate that.
  • Per-partition throughput is capped at roughly 3,000 read and 1,000 write units, so a hot key throttles even when the table has spare capacity overall, and the only real fix is changing the key design to spread the load.
  • Items are limited to 400 KB and query results paginate at 1 MB, so large or list-shaped data has to be split, offloaded to S3 with a pointer, or read through pagination loops that complicate every consumer.
  • It runs only on AWS and the API is proprietary rather than a standard, so moving the data layer means rewriting it; ScyllaDB's Alternator is the only meaningfully compatible target and it brings a much smaller ecosystem.

Pricing, plan by plan

Azure SQL

Free

No published plan breakdown. See the Azure SQL review.

DynamoDB

Free
  • On-Demand Capacity$null/usage-based
    • Pay-per-request pricing with automatic scaling
    • Read: 0.5 RRU per 4 KB (eventually consistent), 1 RRU per 4 KB (strongly consistent), 2 RRU per 4 KB (transactional)
    • Write: 1 WRU per 1 KB
  • Provisioned Capacity$null/hourly
    • Fixed hourly charges based on reserved capacity
    • RCU rate: $0.00013 per hour (Standard)
    • WCU rate: $0.00065 per hour (Standard)
  • Standard Table Class Storage$0.25/per GB/month
    • $0.25 per GB/month after free tier
    • First 25 GB free per month (free tier)
  • Standard-Infrequent Access Table Class$0.1/per GB/month
    • $0.10 per GB/month

Which should you pick?

Choose Azure SQL if

  • You need intelligent performance.
  • You want to start without paying.
  • You work on Cloud (Microsoft Azure).
  • You also want advanced security.
Azure SQL review

Choose DynamoDB if

  • You need managed and serverless.
  • You want to start without paying.
  • You work on AWS.
  • You also want predictable latency.
DynamoDB review

Questions people ask

Is Azure SQL or DynamoDB better?
Neither clearly leads. Azure SQL starts at Free and DynamoDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Azure SQL or DynamoDB?
Azure SQL starts at Free and DynamoDB at Free.
Does Azure SQL or DynamoDB run on more platforms?
Azure SQL runs on Cloud (Microsoft Azure). DynamoDB runs on AWS.
Can I use Azure SQL for free?
Both have a free tier, so you can try either at no cost before committing.
What is Azure SQL best used for?
Azure SQL is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what DynamoDB is typically brought in for.
What can Azure SQL do that DynamoDB cannot?
Azure SQL covers Intelligent Performance, Advanced Security, Hyperscale, Serverless Compute. DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes.

Answered from the vendors’ own pages

Azure SQL: Does Azure SQL Database offer a free tier?

Yes, Azure SQL Database includes a permanent free tier that provides 100,000 vCore seconds, 32 GB of data storage, and 32 GB of backup storage per month. This free tier is available for the lifetime of any Azure subscription with no expiration.

Source
DynamoDB: On-demand or provisioned capacity?

On-demand suits unpredictable or spiky traffic and removes capacity planning. Provisioned with autoscaling is considerably cheaper for steady high-volume workloads. Tables can be switched between them, though not arbitrarily often.

Azure SQL: What pricing models does Azure SQL Database support?

Azure SQL Database offers consumption-based pricing where you pay for resources used, with no long-term commitments required. Database Savings Plans launched in March 2026 allow committing to a fixed hourly amount and save up to 35% across Azure database services.

Source
DynamoDB: Can I run DynamoDB outside AWS?

No. DynamoDB Local exists for development and testing only. For a production-compatible alternative elsewhere, ScyllaDB's Alternator implements the DynamoDB API, but it is a different system with a different ecosystem.

Azure SQL: Is Azure SQL Database compatible with on-premises SQL Server?

Yes, Azure SQL Database shares the same Database Engine as on-premises SQL Server. Existing databases maintain their compatibility level and continue to work after upgrades. Azure SQL Managed Instance provides even broader SQL Server compatibility dating back to SQL Server 2008.

Source
DynamoDB: Can I run ad hoc queries or analytics?

Not on the table itself. Scans are slow and expensive at scale. The usual pattern is to export to S3 or stream changes out and query them in Athena, Redshift or another analytical engine.

Azure SQL: What high availability features does Azure SQL Database provide?

Azure SQL Database provides automatic backups, geo-replication for disaster recovery, failover groups for automatic failover, and zone redundancy for enhanced availability. The service maintains a 99.99% availability SLA for Business Critical tier.

Source
DynamoDB: Is single-table design necessary?

It is the pattern that gets the most from DynamoDB when access patterns are well known, because it lets related items be retrieved in one query. It also makes the model harder to evolve, so many teams reasonably choose multiple simpler tables and accept extra requests.

Azure SQL: Can I use AI features with Azure SQL Database?

Yes, Azure SQL Database includes Copilot for database tasks, Intelligent Applications support, REST API endpoints for building applications, and GraphQL endpoints for modern app development.

Source
DynamoDB: What are the real limits I should design around?

400 KB per item, 1 MB per query or scan page, 100 items per transaction, roughly 3,000 read and 1,000 write units per partition, and eventual consistency on global secondary indexes.

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