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Databases · head to head

DynamoDB vs Immuta

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
Immuta logo

Immuta

Databases

Attribute-based access control and masking applied inside Snowflake, Databricks and BigQuery

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only DynamoDB has a free tier, so it costs nothing to try first.
  • 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.; Immuta contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate.
  • They diverge on capability: DynamoDB covers Managed and serverless, Immuta covers Attribute-based policy.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which DynamoDB and Immuta actually diverge.

Attributes where DynamoDB and Immuta differ
AttributeDynamoDBImmuta
Starting priceFreeOn request
Pricing modelusage-basedquote
Free tierYesNo
PlatformsAWSWeb, API, Cloud
Founded2006Unknown

Identical on both: 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 Immuta

  • Attribute-based policy
  • Native enforcement
  • Dynamic masking
  • Row-level filtering
  • Purpose-based access
  • Sensitive data tagging
  • Audit logging
  • Multi-platform

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 Immuta
  • Traffic that spikes unpredictably, where on-demand capacity absorbs a burst without a capacity-planning exercisenot Immuta
  • Serverless applications on Lambda, where an HTTP-based datastore avoids the connection pooling problem relational databases havenot Immuta
  • Event or telemetry ingestion where writes vastly outnumber reads and each record is retrieved by a known identifiernot Immuta

Immuta

  • A bank whose Snowflake estate has grown to tens of thousands of roles that no one can review before an auditnot DynamoDB
  • A healthcare analytics team that must let researchers query patient data with identifiers masked unless a specific purpose is recordednot DynamoDB
  • A multinational applying different residency and access rules per jurisdiction to the same tables without duplicating datasetsnot DynamoDB
  • An organisation running both Snowflake and Databricks that wants one policy set rather than two divergent implementationsnot 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.

Immuta

  • Contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate.
  • Policy is only as good as the data classification underneath it, so an organisation with poorly tagged columns will spend months on classification before Immuta enforces anything useful.
  • Native enforcement means capability varies by platform, and a feature available on Snowflake may be absent or behave differently on BigQuery, which undermines the promise of one policy set everywhere.
  • Adding an access governance layer creates a new dependency in the path to data: a misconfigured policy silently returns fewer rows rather than erroring, and analysts can act on incomplete results without noticing.
  • It governs cloud data platforms, so personal data in operational databases, files and SaaS applications sits outside its scope and needs separate controls, meaning Immuta is rarely the whole answer.

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

Immuta

On request
  • Immuta Platform$undefined/year
    • Attribute-based policy authoring
    • Native enforcement in supported data platforms
    • Dynamic masking and row-level security

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.
DynamoDB review

Choose Immuta if

  • You need attribute-based policy.
  • You work on Web, API, Cloud.
  • You also want native enforcement.
Immuta review

Questions people ask

Is DynamoDB or Immuta better?
Neither clearly leads. DynamoDB starts at Free and Immuta at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DynamoDB or Immuta?
DynamoDB has a free tier; the other does not. Paid plans start at Free for DynamoDB and On request for Immuta.
Does DynamoDB or Immuta run on more platforms?
DynamoDB runs on AWS. Immuta runs on Web, API, Cloud.
Can I use DynamoDB for free?
Yes. DynamoDB has a free tier, so you can try it without paying. Immuta starts at On request.
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 Immuta is typically brought in for.
What can DynamoDB do that Immuta cannot?
DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes. Immuta covers Attribute-based policy, Native enforcement, Dynamic masking, Row-level filtering.

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.

Immuta: Does Immuta sit in the query path?

No. It compiles policies into the data platform's own native controls, so queries run at normal speed through your existing tools.

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.

Immuta: What does it cost?

Not published. Market data suggests roughly 100,000 to 200,000 US dollars a year for mid-market deployments and considerably more at enterprise scale.

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.

Immuta: Is Immuta still independent?

Yes. It remains independently owned, unlike several competitors in data access governance that have been acquired.

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.

Immuta: Does it work across more than one warehouse?

Yes, one policy set can target Snowflake, Databricks, BigQuery and Starburst, though enforcement capability varies by platform.

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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