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Databases · head to head

DynamoDB vs RisingWave

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
RisingWave logo

RisingWave

Databases

Streaming database that maintains incremental materialised views in SQL instead of Flink jobs

From
Free
Rated
-
Full reviewWebsite

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.; RisingWave anything that does not fit SQL, such as custom windowing, complex event processing or heavy stateful logic, still needs Flink, so RisingWave often adds a system rather than removing one.
  • They diverge on capability: DynamoDB covers Managed and serverless, RisingWave covers SQL materialised views.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which DynamoDB and RisingWave actually diverge.

Attributes where DynamoDB and RisingWave differ
AttributeDynamoDBRisingWave
Pricing modelusage-basedPer RisingWave Unit hour
PlatformsAWSLinux, Docker, Kubernetes, Cloud
Founded2006Unknown

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 RisingWave

  • SQL materialised views
  • Postgres wire compatibility
  • Object storage state
  • Source connectors
  • Sink connectors
  • Iceberg tables
  • Watermarks and windowing
  • User defined functions

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

RisingWave

  • A team with Kafka topics that needs continuously fresh aggregates for a dashboard without standing up a Flink clusternot DynamoDB
  • A fraud or risk team maintaining rolling counters and joins across event streams expressed as SQL viewsnot DynamoDB
  • A company doing Postgres CDC into a real-time denormalised view for search or servingnot DynamoDB
  • An analytics group that wants streaming results landed directly into Apache Iceberg without a separate writer jobnot 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.

RisingWave

  • Anything that does not fit SQL, such as custom windowing, complex event processing or heavy stateful logic, still needs Flink, so RisingWave often adds a system rather than removing one.
  • The Apache 2.0 community edition excludes premium features behind a licence key, and which capabilities sit on which side of that line moves between releases, so a self-hosted plan can be invalidated by an upgrade.
  • Long-running materialised views accumulate state in object storage, and cost and recovery time grow with retention in ways that are hard to forecast before you are in production.
  • The Postgres compatibility is protocol level; it is not a transactional Postgres and using it as a general purpose database, with point updates or high write concurrency, goes badly.
  • It is a comparatively young venture-funded project competing with Flink, Materialize and warehouse-native streaming, and the ecosystem of connectors, operators and third-party expertise is much thinner.

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

RisingWave

Free
  • Community EditionFree
    • Apache 2.0 licence, self-hosted
    • Core streaming engine and connectors
    • Premium features excluded and require a licence key
  • Cloud Basic$0.227/hour
    • Billed per RisingWave Unit hour
    • Hosted on AWS, GCP or Azure
    • Capped at 64 cores
  • Cloud Pro$undefined/year
    • No core limit
    • Bring your own cloud option
    • Premium features included
  • Self-managed Enterprise$undefined/year
    • On premises or Kubernetes
    • Premium features unlocked by licence
    • Annual contract with SLA

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 RisingWave if

  • You need sql materialised views.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Cloud.
  • You also want postgres wire compatibility.
RisingWave review

Questions people ask

Is DynamoDB or RisingWave better?
Neither clearly leads. DynamoDB starts at Free and RisingWave at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DynamoDB or RisingWave?
DynamoDB starts at Free and RisingWave at Free.
Does DynamoDB or RisingWave run on more platforms?
DynamoDB runs on AWS. RisingWave runs on Linux, Docker, Kubernetes, Cloud.
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 RisingWave is typically brought in for.
What can DynamoDB do that RisingWave cannot?
DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes. RisingWave covers SQL materialised views, Postgres wire compatibility, Object storage state, Source connectors.

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.

RisingWave: Is RisingWave open source?

The community edition is Apache 2.0 and self-hostable, but a set of premium features requires a paid licence key.

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.

RisingWave: What does the cloud cost?

It starts at 0.227 US dollars per RisingWave Unit hour on the Basic tier, which is capped at 64 cores.

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.

RisingWave: Does it replace Flink?

For SQL-expressible transformations, often yes. For custom stateful processing and complex event handling, no.

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.

RisingWave: Can I query it like Postgres?

Yes over the Postgres wire protocol, but it is an analytical streaming engine, not a transactional database.

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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