Databases · head to head
DynamoDB vs Firestore

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

Firestore
Databases
Flexible, scalable NoSQL cloud database from Firebase
- 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.; Firestore the no-cost Spark plan caps Standard edition at 50,000 document reads, 20,000 writes and 20,000 deletes per day
- They diverge on capability: DynamoDB covers Managed and serverless, Firestore covers Document Model.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which DynamoDB and Firestore actually diverge.
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 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 Firestore
- Document Model
- Real-time Updates
- Offline Support
- ACID Transactions
- Expressive Queries
- Multi-region
- Security Rules
- Firebase Auth
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 Firestore
- Traffic that spikes unpredictably, where on-demand capacity absorbs a burst without a capacity-planning exercisenot Firestore
- Serverless applications on Lambda, where an HTTP-based datastore avoids the connection pooling problem relational databases havenot Firestore
- Event or telemetry ingestion where writes vastly outnumber reads and each record is retrieved by a known identifiernot Firestore
Firestore
- Storing structured application data with realtime listenersnot DynamoDB
- Backing mobile and web apps with a serverless document databasenot DynamoDB
- Building offline first apps that sync when connectivity returnsnot 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.
Firestore
- The no-cost Spark plan caps Standard edition at 50,000 document reads, 20,000 writes and 20,000 deletes per day
- The Spark plan caps storage at 1 GiB and network egress at 10 GiB per month
- Charging is per document read, so a query returning many documents bills for every one of them
- Going beyond the free thresholds requires the pay as you go Blaze plan billed at Google Cloud rates with no fixed monthly ceiling
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
Firestore
Free- SparkFree
- 1GB storage
- 50K reads/day
- 20K writes/day
- BlazeFree
- Pay as you go
- Unlimited operations
- Multi-region
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 Firestore if
- You need document model.
- You want to start without paying.
- You work on Web, Ios, Android, Flutter.
- You also want real-time updates.
Questions people ask
- Is DynamoDB or Firestore better?
- Neither clearly leads. DynamoDB starts at Free and Firestore at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, DynamoDB or Firestore?
- DynamoDB starts at Free and Firestore at Free.
- Does DynamoDB or Firestore run on more platforms?
- DynamoDB runs on AWS. Firestore runs on Web, Ios, Android, Flutter.
- 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 Firestore is typically brought in for.
- What can DynamoDB do that Firestore cannot?
- DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes. Firestore covers Document Model, Real-time Updates, Offline Support, ACID Transactions.
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.
Firestore: What are the free limits on Cloud Firestore?
The Spark Plan includes 1 GiB of stored data, 50,000 reads per day, 20,000 writes per day, and 20,000 deletes per day at no cost.
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.
Firestore: What happens when I exceed the Spark Plan free tier?
Exceeding the free tier requires upgrading to the Blaze Plan, which bills based on actual usage through Google Cloud pricing. Charges apply for reads, writes, deletes, and data storage.
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.
Firestore: Can I use Firestore without a credit card?
Yes, you can use the Spark Plan indefinitely without a credit card. To use the Blaze Plan (pay-as-you-go), a credit card is required.
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.
Firestore: Is there a trial period for Cloud Firestore?
No trial period is specified. The Spark Plan free tier serves as the trial, with no time limit.
SourceDynamoDB: 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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