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Databases · head to head

DuckDB vs Steampipe

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
Steampipe logo

Steampipe

Developer Tools

Query cloud APIs, SaaS tools and code with SQL, with no extract or load step

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Steampipe aGPL-3.0 across all four engines is a procurement blocker at organisations that ban the licence outright, and the network clause reaches any internal portal or service that puts a web interface in front of it.
  • They diverge on capability: DuckDB covers In-process execution, Steampipe covers SQL over live APIs.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which DuckDB and Steampipe actually diverge.

Attributes where DuckDB and Steampipe differ
AttributeDuckDBSteampipe
Pricing modelopen-sourceOpen source, with paid hosting through Turbot Pipes
PlatformsLinux, macOS, Windows, WebAssemblymacOS, Linux, Windows, Docker, Web
CategoryDatabasesDeveloper Tools
Founded2019Unknown

Identical on both: starting price (Free), 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
  • Vectorised columnar engine
  • Direct file querying
  • Zero dependencies
  • Larger-than-memory queries
  • MIT licence
  • Postgres-flavoured SQL
  • Extension ecosystem

Only in Steampipe

  • SQL over live APIs
  • Wide plugin set
  • Embedded Postgres
  • Compliance benchmarks
  • Joins across providers
  • Hosted option

What people use each for

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

DuckDB

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

Steampipe

  • Security teams answering posture questions against live cloud accounts rather than a nightly exportnot DuckDB
  • Compliance evidence gathering where the answer must reflect the account at the moment it is askednot DuckDB
  • Inventory and drift questions spanning several cloud providers in one querynot DuckDB
  • Engineers who would rather write SQL than learn each provider command line toolnot DuckDB

Where each one falls short

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

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.

Steampipe

  • AGPL-3.0 across all four engines is a procurement blocker at organisations that ban the licence outright, and the network clause reaches any internal portal or service that puts a web interface in front of it.
  • Dashboards, benchmarks and mods were removed from Steampipe entirely at version 1.0 in October 2024 and now live in a separate product, so pre-2024 documentation and tutorials describe commands that no longer exist.
  • Live querying is bound by cloud provider API rate limits and keeps no persistent store by default, which is why a separate DuckDB-backed product exists for log volumes and why large accounts return slowly.
  • The company is fifteen people and bootstrapped, maintaining four command line tools plus a hosted service plus two further products, and the newer tools have thin community traction relative to that surface area.
  • Hosted tiers include only three users regardless of tier, with additional Enterprise users charged separately, so a team of thirty costs an order of magnitude more than the headline figure before compute and storage are counted.

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Steampipe

Free
  • Steampipe CLIFree
    • AGPL-3.0
    • All plugins
    • No user or query limits
  • Pipes DeveloperFree
    • One user
    • 400 compute minutes
    • 3GB storage
  • Pipes Team$49/month
    • Three users
    • 2,000 compute minutes
    • 20GB storage
  • Pipes Enterprise$249/month
    • Three users
    • 10,000 compute minutes
    • 100GB storage

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 vectorised columnar engine.
DuckDB review

Choose Steampipe if

  • You need sql over live apis.
  • You want to start without paying.
  • You work on macOS, Linux, Windows, Docker, Web.
  • You also want wide plugin set.
Steampipe review

Questions people ask

Is DuckDB or Steampipe better?
Neither clearly leads. DuckDB starts at Free and Steampipe at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Steampipe?
DuckDB starts at Free and Steampipe at Free.
Does DuckDB or Steampipe run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Steampipe runs on macOS, Linux, Windows, Docker, Web.
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 transformation steps in a data pipeline that would otherwise need spark, replaced by sql over parquet in a single process, analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptable, local exploration of files that are too large for a pandas dataframe but far too small to justify a warehouse, continuous integration and testing of analytical sql, where a real engine can run in the test process without provisioning anything. Of those, transformation steps in a data pipeline that would otherwise need spark, replaced by sql over parquet in a single process and analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptable are not what Steampipe is typically brought in for.
What can DuckDB do that Steampipe cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Steampipe covers SQL over live APIs, Wide plugin set, Embedded Postgres, Compliance benchmarks.

Answered from the vendors’ own pages

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.

Steampipe: When did Steampipe become AGPL?

May 2021, about four months after the project went public. It is a settled licence rather than a recent change, and predates the Business Source Licence wave it is often confused with.

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.

Steampipe: Where did the dashboards and benchmarks go?

Into Powerpipe. They were deprecated in March 2024 and removed from Steampipe at version 1.0 in October 2024, so the check, dashboard, mod and variable commands are gone.

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.

Steampipe: Is it fast on a large cloud estate?

Not always. Queries call provider APIs at request time, so rate limits rather than query planning set the pace, and there is no persistent store by default.

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.

Steampipe: Does the AGPL affect internal use?

Running it internally for your own analysis is fine. Putting a web interface in front of it that other people use is where the network clause becomes a question for your legal team.

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.

Steampipe: Is a bootstrapped vendor a risk?

It cuts both ways. There is no investor pressure toward a licence change or an exit, and there are also fifteen people supporting a large product surface.

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