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Databases · head to head

Amazon RDS vs DuckDB

Amazon RDS logo

Amazon RDS

Databases

Set up, operate, and scale a relational database in the cloud

From
Free
Rated
-
Full reviewWebsite
DuckDB logo

DuckDB

Databases

MIT-licensed analytical SQL database that runs inside your process, with no server, no dependencies and one writer at a time.

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Amazon RDS no super-user access or direct host connectivity limits advanced customization; DuckDB a database file accepts one read-write process at a time; other processes must open it read-only and will not see subsequent writes, so DuckDB cannot be the shared database behind several services.
  • They diverge on capability: Amazon RDS covers Multiple DB Engines, DuckDB covers In-process execution.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Amazon RDS and DuckDB actually diverge.

Attributes where Amazon RDS and DuckDB differ
AttributeAmazon RDSDuckDB
Pricing modelusage-basedopen-source
PlatformsAWS Cloud, Multi-AZ, Multi-regionLinux, macOS, Windows, WebAssembly
Founded20062019

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 Amazon RDS

  • Multiple DB Engines
  • Automated Backups
  • Multi-AZ Deployment
  • Read Replicas
  • Encryption
  • Performance Insights
  • Automatic Scaling
  • MySQL

Only in DuckDB

  • In-process execution
  • Vectorised columnar engine
  • Direct file querying
  • Zero dependencies
  • Larger-than-memory queries
  • MIT licence
  • Postgres-flavoured SQL
  • Extension ecosystem

What people use each for

The jobs each tool is most often brought in to do.

Amazon RDS

  • Transaction processingnot DuckDB
  • Data storagenot DuckDB
  • Application backendnot DuckDB
  • Reportingnot DuckDB
  • Data analyticsnot DuckDB

DuckDB

  • Transformation steps in a data pipeline that would otherwise need Spark, replaced by SQL over Parquet in a single processnot Amazon RDS
  • Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot Amazon RDS
  • Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot Amazon RDS
  • Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot Amazon RDS

Where each one falls short

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

Amazon RDS

  • No super-user access or direct host connectivity limits advanced customization
  • Pricing unpredictable and expensive compared to GCP alternatives with equivalent features
  • Limited access to system procedures and tables requiring advanced permissions
  • No Oracle RAC (Real Application Clusters) support for high-availability Oracle deployments

DuckDB

  • A database file accepts one read-write process at a time; other processes must open it read-only and will not see subsequent writes, so DuckDB cannot be the shared database behind several services.
  • There is no network protocol, authentication or user management, so exposing it to remote clients means writing and securing your own service around it.
  • It is built for scans and aggregations, not for many small transactions, so a workload of high-frequency single-row inserts and updates performs badly compared with SQLite or Postgres.
  • Storage files are backwards compatible but not forwards compatible, so a file written by a newer version cannot be read by an older one and every consumer of a shared file must be upgraded together.
  • Query memory settings matter: some operations still need to hold significant state, so an under-configured memory limit turns a large join or a high-cardinality aggregation into a spill-heavy query or an out-of-memory failure rather than a slow success.

Pricing, plan by plan

Amazon RDS

Free
  • On-Demand Instances$undefined/per second
  • Reserved Instances$undefined/mo
  • Database Savings Plans$undefined/mo

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Which should you pick?

Choose Amazon RDS if

  • You need multiple db engines.
  • You want to start without paying.
  • You work on AWS Cloud, Multi-AZ, Multi-region.
  • You also want automated backups.
Amazon RDS review

Choose DuckDB if

  • You need in-process execution.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, WebAssembly.
  • You also want vectorised columnar engine.
DuckDB review

Questions people ask

Is Amazon RDS or DuckDB better?
Neither clearly leads. Amazon RDS starts at Free and DuckDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon RDS or DuckDB?
Amazon RDS starts at Free and DuckDB at Free.
Does Amazon RDS or DuckDB run on more platforms?
Amazon RDS runs on AWS Cloud, Multi-AZ, Multi-region. DuckDB runs on Linux, macOS, Windows, WebAssembly.
Can I use Amazon RDS for free?
Both have a free tier, so you can try either at no cost before committing.
What is Amazon RDS best used for?
Amazon RDS is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what DuckDB is typically brought in for.
What can Amazon RDS do that DuckDB cannot?
Amazon RDS covers Multiple DB Engines, Automated Backups, Multi-AZ Deployment, Read Replicas. DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies.

Answered from the vendors’ own pages

Amazon RDS: What is included in the AWS Free Tier for RDS?

For signups before July 15, 2025: 750 hours per month of single-AZ database instance usage (12 months), 20 GB General Purpose SSD storage monthly, 20 GB automated backup storage monthly, available engines include MySQL, MariaDB, PostgreSQL, SQL Server Express Edition. For signups after July 15, 2025: choice between Free Plan or Paid Plan, $100 in credits plus up to $100 additional credits for activating foundational services, credits valid 12 months. Free Tier unavailable in AWS GovCloud (US) and China (Beijing) regions.

Source
DuckDB: Can multiple applications share one DuckDB database?

Not for writing. One process holds the database read-write; others may attach read-only and will not see later writes. Shared multi-writer access needs a different database or a table format with a catalogue.

Amazon RDS: How is data transfer priced in RDS?

Same Availability Zone (EC2 to RDS) is free. Multi-AZ replication is free. Cross-AZ within same region is 0.01 USD per GB in and out. Cross-region snapshots and backups follow standard data transfer charges.

Source
DuckDB: Is it a replacement for a data warehouse?

For single-node analytical workloads up to a few hundred gigabytes it very often is. It is not a replacement when many concurrent users need a shared, governed, always-on service.

Amazon RDS: What database engines are supported by RDS?

Aurora, MySQL, PostgreSQL, MariaDB, Oracle, SQL Server, and IBM Db2. Pricing varies by engine.

Source
DuckDB: Do I have to load data into it?

No. It queries Parquet, CSV, JSON and Arrow in place, including on object storage. Its own storage format is optional and mainly useful when you want indexes, constraints and faster repeated access.

Amazon RDS: What cost components are included in RDS monthly pricing?

DB instance hours (billed in 1-second increments, 10-minute minimum), storage per GB per month, I/O requests (Aurora and magnetic storage only), provisioned IOPS per month, backup storage, and data transfer fees.

Source
DuckDB: What is MotherDuck's relationship to it?

MotherDuck is a separate company offering a managed and hybrid service built on the DuckDB engine. DuckDB itself remains MIT-licensed and independent of it, with the IP held by the DuckDB Foundation.

DuckDB: Is it suitable for OLTP?

No. It is designed for analytical scans. For transactional workloads with frequent small writes, SQLite or Postgres is the right tool.

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