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Databases · head to head

Amazon Redshift vs DynamoDB

Amazon Redshift logo

Amazon Redshift

Databases

Fast, scalable cloud data warehouse from AWS

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: Amazon Redshift on-demand pricing runs up to 75% higher than competitors like Snowflake and BigQuery; 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: Amazon Redshift covers Columnar Storage, DynamoDB covers Managed and serverless.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Amazon Redshift and DynamoDB actually diverge.

Attributes where Amazon Redshift and DynamoDB differ
AttributeAmazon RedshiftDynamoDB
PlatformsWebAWS
Founded20122006

Identical on both: starting price (Free), pricing model (usage-based), 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 Amazon Redshift

  • Columnar Storage
  • Massively Parallel
  • Machine Learning
  • AQUA Acceleration
  • Data Sharing
  • Federated Query
  • Concurrency Scaling
  • S3

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.

Amazon Redshift

  • Business intelligencenot DynamoDB
  • Data warehousingnot DynamoDB
  • Real-time analyticsnot DynamoDB
  • Reportingnot DynamoDB
  • Machine learningnot DynamoDB

DynamoDB

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

Where each one falls short

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

Amazon Redshift

  • On-demand pricing runs up to 75% higher than competitors like Snowflake and BigQuery
  • Requires significant manual tuning including managing concurrency scaling costs and configuring Workload Management queues
  • Performance degrades without proper design of distribution keys and sort keys
  • Limited elastic resize options - can only halve or double current cluster size
  • AWS lock-in makes it unsuitable for multi-cloud architectures

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

Amazon Redshift

Free
  • Free TrialFree
    • 750 DC2.Large hours
    • 2 months free
    • Full features
  • On-Demand$0.25/hour
    • Pay per node hour
    • All features
    • Standard 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 Amazon Redshift if

  • You need columnar storage.
  • You want to start without paying.
  • You also want massively parallel.
Amazon Redshift 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 Amazon Redshift or DynamoDB better?
Neither clearly leads. Amazon Redshift 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, Amazon Redshift or DynamoDB?
Amazon Redshift starts at Free and DynamoDB at Free.
Does Amazon Redshift or DynamoDB run on more platforms?
Amazon Redshift runs on Web. DynamoDB runs on AWS.
Can I use Amazon Redshift for free?
Both have a free tier, so you can try either at no cost before committing.
What is Amazon Redshift best used for?
Amazon Redshift is most often used for business intelligence, data warehousing, real-time analytics, reporting. Of those, business intelligence and data warehousing are not what DynamoDB is typically brought in for.
What can Amazon Redshift do that DynamoDB cannot?
Amazon Redshift covers Columnar Storage, Massively Parallel, Machine Learning, AQUA Acceleration. DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes.

Answered from the vendors’ own pages

Amazon Redshift: What deployment options does Amazon Redshift offer?

Redshift offers Provisioned Cluster (with RA3 or DC2 nodes) and Serverless options to match varying workloads. The new Redshift RG instance family, powered by Graviton, delivers 2.4x faster performance than RA3 at 30% lower cost per vCPU.

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.

Amazon Redshift: What does Amazon Redshift cost?

Provisioned cluster pricing: RA3 on-demand starts at $1.086/hour for ra3.xlplus. Serverless costs approximately $0.375 per RPU-hour with 4-RPU minimum (roughly $1.50/hour active workload). Managed storage costs $0.024/GB-month.

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.

Amazon Redshift: Does Redshift work with data lakes?

Yes, Redshift's integrated data lake query engine processes workloads on Apache Iceberg tables and other supported formats in Amazon S3, allowing you to run SQL analytics across your data warehouse and data lake from the same engine.

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.

Amazon Redshift: Is there a free tier for Amazon Redshift?

AWS offers a free trial with $300 USD in Serverless credits valid for 90 days, but Redshift is not part of the permanent AWS Free 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.

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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