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Databases · head to head

Apache Pinot vs DynamoDB

Apache Pinot logo

Apache Pinot

Databases

Real-time distributed OLAP datastore for analytics

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: Apache Pinot self-hosted and distributed, so running it means operating a cluster rather than consuming a service; 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: Apache Pinot covers Real-time Analytics, DynamoDB covers Managed and serverless.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Apache Pinot and DynamoDB actually diverge.

Attributes where Apache Pinot and DynamoDB differ
AttributeApache PinotDynamoDB
Pricing modelopen-sourceusage-based
PlatformsLinux, Docker, KubernetesAWS
Founded19992006

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 Apache Pinot

  • Real-time Analytics
  • Column-oriented
  • Distributed Processing
  • SQL Support
  • Pluggable Indexing
  • Star-tree Index
  • Upsert Support
  • Kafka

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.

Apache Pinot

  • Sub-second analytics queries on freshly ingested datanot DynamoDB
  • User-facing dashboards inside a productnot DynamoDB
  • Real-time metrics at high ingest ratesnot DynamoDB
  • Petabyte-scale analytics as run at LinkedIn and Ubernot DynamoDB

DynamoDB

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

Where each one falls short

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

Apache Pinot

  • Self-hosted and distributed, so running it means operating a cluster rather than consuming a service
  • Managed hosting comes from third parties such as StarTree rather than from the project
  • Built for user-facing real-time OLAP, so it is not a general purpose database

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

Apache Pinot

Free
  • Open SourceFree
    • Real-time analytics
    • SQL queries
    • Horizontal scaling

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 Apache Pinot if

  • You need real-time analytics.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want column-oriented.
Apache Pinot 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 Apache Pinot or DynamoDB better?
Neither clearly leads. Apache Pinot 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, Apache Pinot or DynamoDB?
Apache Pinot starts at Free and DynamoDB at Free.
Does Apache Pinot or DynamoDB run on more platforms?
Apache Pinot runs on Linux, Docker, Kubernetes. DynamoDB runs on AWS.
Can I use Apache Pinot for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Pinot best used for?
Apache Pinot is most often used for sub-second analytics queries on freshly ingested data, user-facing dashboards inside a product, real-time metrics at high ingest rates, petabyte-scale analytics as run at linkedin and uber. Of those, sub-second analytics queries on freshly ingested data and user-facing dashboards inside a product are not what DynamoDB is typically brought in for.
What can Apache Pinot do that DynamoDB cannot?
Apache Pinot covers Real-time Analytics, Column-oriented, Distributed Processing, SQL Support. DynamoDB covers Managed and serverless, Predictable latency, On-demand or provisioned capacity, Global secondary indexes.

Answered from the vendors’ own pages

Apache Pinot: How much does Apache Pinot cost?

Apache Pinot is free and open-source. It is provided under the Apache License, which allows free use, modification, and distribution.

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.

Apache Pinot: Is Apache Pinot free for commercial use?

Yes. Apache Pinot is licensed under the Apache License, which explicitly permits commercial use at no cost.

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.

Apache Pinot: Can I run Apache Pinot locally or with Docker?

Yes. Apache Pinot offers a Docker quickstart and free downloads of the latest version (1.5.1 at the time of the page). You are responsible for hosting and infrastructure.

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.

Apache Pinot: Are there restrictions on how I can use Apache Pinot?

The Apache License permits unrestricted use, but requires retention of license notices and statements. No usage limits or feature restrictions are enforced.

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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