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Databases · head to head

DuckDB vs Apache Spark MLlib

DuckDB logo

DuckDB

Databases

Fast in-process analytical database

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Machine Learning

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: DuckDB client-server setup remains in beta and not recommended for production distributed scenarios; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
  • They diverge on capability: DuckDB covers In-process Execution, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which DuckDB and Apache Spark MLlib actually diverge.

Attributes where DuckDB and Apache Spark MLlib differ
AttributeDuckDBApache Spark MLlib
PlatformsLinux, macOS, Windows, WebAssemblyLinux, macOS, Windows
CategoryDatabasesMachine Learning
Founded20191999

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), user rating (Not yet rated).

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 DuckDB

  • In-process Execution
  • Columnar Storage
  • Vectorized Execution
  • Rich SQL Support
  • Parquet Support
  • CSV/JSON Import
  • Zero Dependencies
  • Python

Only in Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Feature engineering
  • Apache Spark
  • Hadoop
  • Kafka

Both cover

  • Linux support
  • Windows support
  • Mac support

What people use each for

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

DuckDB

  • Analytics and data warehousingnot Apache Spark MLlib
  • OLAP queries and data explorationnot Apache Spark MLlib
  • Data science and machine learning workflowsnot Apache Spark MLlib
  • Multi-format data ingestion and processingnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot DuckDB
  • Data sciencenot DuckDB
  • Distributed computingnot DuckDB

Where each one falls short

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

DuckDB

  • Client-server setup remains in beta and not recommended for production distributed scenarios

Apache Spark MLlib

  • Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

Which should you pick?

Choose DuckDB if

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

Choose Apache Spark MLlib if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want regression.
Apache Spark MLlib review

Questions people ask

Is DuckDB or Apache Spark MLlib better?
Neither clearly leads. DuckDB starts at Free and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Apache Spark MLlib?
DuckDB starts at Free and Apache Spark MLlib at Free.
Does DuckDB or Apache Spark MLlib run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use DuckDB for free?
Both have a free tier, so you can try either at no cost before committing.
What is DuckDB best used for?
DuckDB is most often used for analytics and data warehousing, olap queries and data exploration, data science and machine learning workflows, multi-format data ingestion and processing. Of those, analytics and data warehousing and olap queries and data exploration are not what Apache Spark MLlib is typically brought in for.
What can DuckDB do that Apache Spark MLlib cannot?
DuckDB covers In-process Execution, Columnar Storage, Vectorized Execution, Rich SQL Support. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Linux support, Windows support, Mac support.

Answered from the vendors’ own pages

DuckDB: Is DuckDB free to use?

Yes, DuckDB is completely free. There are no subscription tiers, user limits, or paid plans. The software has zero licensing costs.

Source
Apache Spark MLlib: How much does Apache Spark MLlib cost?

MLlib is completely free and open source, licensed under the Apache License Version 2.0. There are no subscription, licensing, or usage fees.

Source
DuckDB: What license is DuckDB distributed under?

DuckDB is open source under the MIT License, governed by the independent DuckDB Foundation. The MIT License permits commercial use, modification, and distribution with minimal restrictions.

Source
Apache Spark MLlib: What licensing does MLlib use?

MLlib is licensed under Apache License Version 2.0, making it freely available for all users regardless of organization size or use case.

Source
DuckDB: Can I use DuckDB in commercial applications?

Yes, the MIT License allows commercial use without restrictions or requirements to publish proprietary code. You can deploy DuckDB anywhere from edge devices to high-core servers.

Source
Apache Spark MLlib: How do I use MLlib?

MLlib is built into Apache Spark. Download Spark, which includes MLlib as a module, and deploy on your choice of infrastructure including Hadoop, Mesos, Kubernetes, standalone, or cloud.

Source
DuckDB: Are there any limitations on how many instances I can run?

No, there are no user limits, usage limits, or instance restrictions. You have unlimited access to all DuckDB features.

Source
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