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Miller

Free#22 of 36 in Data Transformation Tools

Miller: A free, open-source CLI for streaming transformations across structured data formats. Ranked #22 of 36 in Data Transformation Tools by our editors (7.1/10); pricing: Open source; best for streaming command-line format transformation.

7.1/10Editor score

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At a glance

Editor score
7.1 / 10
Pricing
Open source
Best for
Streaming command-line format transformation
Paid from
Free
Deployment model
Self_hosted
Facts checked
22 Sep 2026

Where it wins
- Supports CSV, JSON, YAML, DCF, and many other formats
- Streams filtering, reshaping, joining, aggregation, and conversion
- Includes a dedicated language for custom transformations
Where it doesn't
- Requires code-based command-line operation
- Self-hosted deployment puts setup responsibility on the operator
- Not positioned for external integrations or orchestration

Our verdict on Miller

Miller is an open-source command-line tool for processing name-indexed and tabular data. It is designed for users working with data cleaning, log processing, statistical reporting, database-query post-processing, and streaming workflows. The tool runs on Windows, macOS, and Linux, and handles formats including CSV, TSV, ASV, USV, JSON, JSON Lines, YAML, PPRINT, Markdown, XTAB, DKVP, DKVPX, NIDX, DCF, and recutils. Its interface is code-based, with pipe-friendly operation suited to Unix-style workflows.

Miller’s main strength is breadth within structured-data transformation. It can convert between supported formats, filter records, select fields, sort, join, group, reshape, aggregate, and report statistics. The Miller domain-specific language extends those operations with custom transformations. Input checks cover parseability and empty keys, while MCP tools support capability discovery, DSL validation, data description, and command execution. This combination makes Miller a practical fit when transformations need to be repeatable, composable, and expressed as commands or scripts rather than managed through a visual interface.

The published positioning centers on a free, open-source tool distributed as a command-line binary rather than a hosted service, so there are no paid tiers shaping its feature set. The self-hosted model suits technical teams that want local control and streaming execution, but it places installation, workflow design, and operational responsibility with the user. Miller is a strong choice for format conversion and structured-data processing in shell-based pipelines. Teams seeking hosted orchestration or a non-code transformation interface should choose a different type of product.

Your product? Our editors can test Miller in depth and publish a review, labelled as paid · from $149/mo →

Miller pricing

Plans Open sourceFree Free to use — no paid tier required for the core job.

See plans on miller.readthedocs.io

Miller fact sheet

Free plan	Not verified
Paid from	Free
Deployment model	Self_hosted
Transformation interface	Code
Supported data formats	CSV, TSV, ASV, USV, JSON, JSON Lines, YAML, PPRINT, Markdown, XTAB, DKVP, DKVPX, NIDX, DCF, recutils
Version control	Not verified
Workflow orchestration	Not verified
Data quality checks	Yes
Deployment	Self-hosted, Desktop
Platforms	Windows, macOS, Linux
Support	Docs, Community
Built for	Solo, Small business, Mid-market (editorial estimate)
Pricing	Open source
Website	miller.readthedocs.io
Facts checked	22 Sep 2026

Alternatives to Miller

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Featured on iTechGuides

Miller is listed in our Data Transformation Tools directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.

Last updated 7 Oct 2026 · How we research and update