Databases · head to head
DataStax vs DynamoDB

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: DataStax dataStax's own Astra DB documentation states the Enterprise plan is an annual, contract-based plan with negotiated pricing, meaning list prices are not published for that tier; 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: DataStax covers Cassandra Compatible, DynamoDB covers Managed and serverless.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which DataStax and DynamoDB 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 DataStax
- Cassandra Compatible
- Vector Search
- Serverless
- Multi-cloud
- Streaming
- CDC
- GraphQL API
- LangChain
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.
DataStax
- Real-time applicationsnot DynamoDB
- Content managementnot DynamoDB
- User profilesnot DynamoDB
- Mobile backendsnot DynamoDB
- Cachingnot DynamoDB
DynamoDB
- High-volume keyed workloads such as sessions, shopping carts, device state or user profiles where the access pattern is fixed and knownnot DataStax
- Traffic that spikes unpredictably, where on-demand capacity absorbs a burst without a capacity-planning exercisenot DataStax
- Serverless applications on Lambda, where an HTTP-based datastore avoids the connection pooling problem relational databases havenot DataStax
- Event or telemetry ingestion where writes vastly outnumber reads and each record is retrieved by a known identifiernot DataStax
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
DataStax
- DataStax's own Astra DB documentation states the Enterprise plan is an annual, contract-based plan with negotiated pricing, meaning list prices are not published for that tier
- DataStax's Astra DB documentation directs Standard plan customers to IBM's watsonx.data pricing for exact consumption-based rates following the DataStax/IBM deal, rather than publishing them on DataStax's own site
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
DataStax
Free- FreeFree
- 5GB storage
- 40M read/write ops
- Vector search
- Pay As You GoFree
- Usage-based pricing
- Multi-region
- Enterprise support
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 DataStax if
- You need cassandra compatible.
- You want to start without paying.
- You work on Web, Aws, Azure, Gcp.
- You also want vector search.
Choose DynamoDB if
- You need managed and serverless.
- You want to start without paying.
- You work on AWS.
- You also want predictable latency.
Questions people ask
- Is DataStax or DynamoDB better?
- Neither clearly leads. DataStax 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, DataStax or DynamoDB?
- DataStax starts at Free and DynamoDB at Free.
- Does DataStax or DynamoDB run on more platforms?
- DataStax runs on Web, Aws, Azure, Gcp. DynamoDB runs on AWS.
- Can I use DataStax for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is DataStax best used for?
- DataStax is most often used for real-time applications, content management, user profiles, mobile backends. Of those, real-time applications and content management are not what DynamoDB is typically brought in for.
- What can DataStax do that DynamoDB cannot?
- DataStax covers Cassandra Compatible, Vector Search, Serverless, Multi-cloud. DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes.
Answered from the vendors’ own pages
DataStax: Is DataStax available as a managed service?
Yes, DataStax is available as Astra DB, a managed database service. Users can sign up for Astra DB directly to create accounts and access the platform.
SourceDynamoDB: 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.
DataStax: How is DataStax priced?
DataStax (now part of IBM) does not publish pricing on its documentation homepage. Pricing information would need to be obtained through the Astra DB signup page or by contacting IBM directly.
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.
DataStax: Is there an enterprise licensing option?
DataStax is now part of IBM. Enterprise customers should contact IBM directly for licensing agreements and enterprise-specific pricing.
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.
DataStax: Can I try DataStax without an account?
To use DataStax Astra DB, account creation is required. The documentation does not mention a free trial or demonstration environment that does not require signup.
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.
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