Databases · head to head
DynamoDB vs Postgres
DynamoDB
Databases
AWS-only managed key-value and document database with fixed per-partition throughput limits and no ad hoc queries.
- From
- Free
- Rated
- -
The short version
- Each has a real cost: 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.; Postgres each major version is supported for only 5 years after its initial release, after which it is end-of-life
- They diverge on capability: DynamoDB covers Managed and serverless, Postgres covers ACID compliance.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which DynamoDB and Postgres actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
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 DynamoDB
- Managed and serverless
- Predictable latency
- On-demand or provisioned capacity
- Global secondary indexes
- Transactions
- DynamoDB Streams
- Global tables
- Point-in-time recovery
Only in Postgres
- ACID compliance
- Complex queries
- Foreign keys
- Triggers
- Views
- Stored procedures
- JSON/JSONB support
- Full-text search
What people use each for
The jobs each tool is most often brought in to do.
DynamoDB
- High-volume keyed workloads such as sessions, shopping carts, device state or user profiles where the access pattern is fixed and knownnot Postgres
- Traffic that spikes unpredictably, where on-demand capacity absorbs a burst without a capacity-planning exercisenot Postgres
- Serverless applications on Lambda, where an HTTP-based datastore avoids the connection pooling problem relational databases havenot Postgres
- Event or telemetry ingestion where writes vastly outnumber reads and each record is retrieved by a known identifiernot Postgres
Postgres
- Running a general purpose relational database for applicationsnot DynamoDB
- Self-hosting an open source SQL database with no licence feenot DynamoDB
- Workloads needing extensions, JSON and full text search in one enginenot DynamoDB
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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.
Postgres
- Each major version is supported for only 5 years after its initial release, after which it is end-of-life
- Major version upgrades break on-disk compatibility and require a full dump and reload or the pg_upgrade tool
- New major versions ship about once a year, so staying supported means a disruptive upgrade cycle
- Minor releases contain only frequently-encountered bug fixes, low-risk fixes, security issues and data corruption fixes, so feature gaps are not addressed within a major version
- There is no vendor SLA; commercial support must be bought separately from third party professional services listed by the project
Pricing, plan by plan
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
Postgres
Free- Community EditionFree
- Full database features
- No limitations
- Community support
Which should you pick?
Choose DynamoDB if
- You need managed and serverless.
- You want to start without paying.
- You work on AWS.
- You also want predictable latency.
Choose Postgres if
- You need acid compliance.
- You want to start without paying.
- You work on Linux, Windows, Macos, Docker.
- You also want complex queries.
Questions people ask
- Is DynamoDB or Postgres better?
- Neither clearly leads. DynamoDB starts at Free and Postgres at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, DynamoDB or Postgres?
- DynamoDB starts at Free and Postgres at Free.
- Does DynamoDB or Postgres run on more platforms?
- DynamoDB runs on AWS. Postgres runs on Linux, Windows, Macos, Docker.
- Can I use DynamoDB for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is DynamoDB best used for?
- DynamoDB is most often used for high-volume keyed workloads such as sessions, shopping carts, device state or user profiles where the access pattern is fixed and known, traffic that spikes unpredictably, where on-demand capacity absorbs a burst without a capacity-planning exercise, serverless applications on lambda, where an http-based datastore avoids the connection pooling problem relational databases have, event or telemetry ingestion where writes vastly outnumber reads and each record is retrieved by a known identifier. Of those, high-volume keyed workloads such as sessions, shopping carts, device state or user profiles where the access pattern is fixed and known and traffic that spikes unpredictably, where on-demand capacity absorbs a burst without a capacity-planning exercise are not what Postgres is typically brought in for.
- What can DynamoDB do that Postgres cannot?
- DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes. Postgres covers ACID compliance, Complex queries, Foreign keys, Triggers.
Answered from the vendors’ own pages
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.
Postgres: How much does PostgreSQL cost to use?
PostgreSQL is completely free to download, install, and use. No licensing fees, subscription costs, or per-seat charges apply. The database is open source under the PostgreSQL License. Source: https://www.postgresql.org
SourceDynamoDB: 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.
Postgres: Are there commercial PostgreSQL support options available?
Official PostgreSQL (the project) is free. Commercial PostgreSQL services such as hosting, professional support, training, and managed database services are offered by third-party vendors, not the PostgreSQL project itself. Source: https://www.postgresql.org
SourceDynamoDB: 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.
Postgres: Do I need a license to use PostgreSQL commercially?
No. PostgreSQL is open source under the PostgreSQL License, which permits free commercial use without royalties, licensing fees, or support obligations. Source: https://www.postgresql.org
SourceDynamoDB: 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.
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.
Related pages
Other head to heads
- DynamoDB vs Elasticsearch
- DynamoDB vs Cassandra
- DynamoDB vs Cockroach Labs
- DynamoDB vs Airtable
- DynamoDB vs PostgreSQL
- DynamoDB vs BigQuery
- DynamoDB vs FaunaDB
- DynamoDB vs Memcached
- DynamoDB vs ScyllaDB
- DynamoDB vs PlanetScale
- DynamoDB vs Couchbase
- DynamoDB vs CosmosDB
- DynamoDB vs DataStax
- DynamoDB vs dbt
- DynamoDB vs EMQX
- DynamoDB vs Firebase Realtime Database
- DynamoDB vs CouchDB
- DynamoDB vs Linear
- DynamoDB vs Asana
- DynamoDB vs ClickUp
- DynamoDB vs Figma
- DynamoDB vs Supabase
- DynamoDB vs Redis
- DynamoDB vs Aha!
- DynamoDB vs Eclipse
- DynamoDB vs Excalidraw
- DynamoDB vs MongoDB
- DynamoDB vs Okta
- DynamoDB vs Notion
- DynamoDB vs Close
- DynamoDB vs Coda
- DynamoDB vs Drift
- DynamoDB vs JetBrains IntelliJ IDEA
- DynamoDB vs LogRocket
- DynamoDB vs Neovim
- Postgres vs Elasticsearch
- Postgres vs Cassandra
- Postgres vs Cockroach Labs
- Postgres vs Airtable
- Postgres vs PostgreSQL
- Postgres vs BigQuery
- Postgres vs FaunaDB
- Postgres vs Memcached
- Postgres vs ScyllaDB
- Postgres vs PlanetScale
- Postgres vs Couchbase
- Postgres vs CosmosDB
- Postgres vs DataStax
- Postgres vs dbt
- Postgres vs EMQX
- Postgres vs Firebase Realtime Database
- Postgres vs CouchDB
- Postgres vs Linear
- Postgres vs Asana
- Postgres vs ClickUp
- Postgres vs Figma
- Postgres vs Supabase
- Postgres vs Redis
- Postgres vs Aha!
- Postgres vs Eclipse
- Postgres vs Excalidraw
- Postgres vs MongoDB
- Postgres vs Okta
- Postgres vs Notion
- Postgres vs Close
- Postgres vs Coda
- Postgres vs Drift
- Postgres vs JetBrains IntelliJ IDEA
- Postgres vs LogRocket
- Postgres vs Neovim