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Cassandra vs DuckDB

Cassandra logo

Cassandra

Databases

Manage massive amounts of data with linear scalability

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: Cassandra no support for joins across tables; 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: Cassandra covers Linear Scalability, DuckDB covers In-process execution.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Cassandra and DuckDB actually diverge.

Attributes where Cassandra and DuckDB differ
AttributeCassandraDuckDB
Pricing modelUnknownopen-source
PlatformsLinux, macOS, Windows, Docker, KubernetesLinux, macOS, Windows, WebAssembly
Founded20082019

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 Cassandra

  • Linear Scalability
  • Fault Tolerance
  • Multi-datacenter Replication
  • Tunable Consistency
  • CQL Query Language
  • Distributed Architecture
  • No Single Point of Failure
  • DataStax

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.

Cassandra

  • Real-time applicationsnot DuckDB
  • Content managementnot DuckDB
  • User profilesnot DuckDB
  • Mobile backendsnot DuckDB
  • Cachingnot DuckDB

DuckDB

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

Where each one falls short

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

Cassandra

  • No support for joins across tables
  • No ACID transactions across multiple rows
  • Data model must be designed around query patterns upfront, making schema evolution difficult
  • Partition key misconfigurations can cause uneven data distribution and hotspots that degrade performance

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

Cassandra

Free

No published plan breakdown. See the Cassandra review.

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Which should you pick?

Choose Cassandra if

  • You need linear scalability.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes.
  • You also want fault tolerance.
Cassandra 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 Cassandra or DuckDB better?
Neither clearly leads. Cassandra 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, Cassandra or DuckDB?
Cassandra starts at Free and DuckDB at Free.
Does Cassandra or DuckDB run on more platforms?
Cassandra runs on Linux, macOS, Windows, Docker, Kubernetes. DuckDB runs on Linux, macOS, Windows, WebAssembly.
Can I use Cassandra for free?
Both have a free tier, so you can try either at no cost before committing.
What is Cassandra best used for?
Cassandra is most often used for real-time applications, content management, user profiles, mobile backends. Of those, real-time applications and content management are not what DuckDB is typically brought in for.
What can Cassandra do that DuckDB cannot?
Cassandra covers Linear Scalability, Fault Tolerance, Multi-datacenter Replication, Tunable Consistency. DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies.

Answered from the vendors’ own pages

Cassandra: Does Cassandra support joins between tables?

No. Cassandra does not support joins or foreign keys. The data model requires denormalization, meaning data must be duplicated across tables to support different query patterns.

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.

Cassandra: Does Cassandra offer ACID transactions?

No. Cassandra provides only row-level atomicity and isolation, not full ACID transactions across multiple rows or tables. It uses lightweight transactions via Paxos for per-row compare-and-set operations.

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.

Cassandra: What programming languages can connect to Cassandra?

Cassandra supports official drivers for multiple languages including Python, Java, Node.js, and Go, allowing applications to communicate via the native Cassandra protocol.

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.

Cassandra: Can I deploy Cassandra in the cloud?

Yes. Cassandra can run on any cloud platform (AWS, Google Cloud, Azure) via Docker, virtual machines, or managed services like DataStax Astra DB, which provides a fully managed DBaaS option.

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.

Cassandra: Does Cassandra have a free option?

The open source Apache Cassandra is free. DataStax also offers Astra DB with a free tier providing up to 25GB storage and 25 million read/write operations per month.

Source
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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