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Databases · head to head

OpenSearch vs Steampipe

OpenSearch logo

OpenSearch

Databases

Open-source search and analytics suite forked from Elasticsearch

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: OpenSearch diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one; 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: OpenSearch covers Full-text search, 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 OpenSearch and Steampipe actually diverge.

Attributes where OpenSearch and Steampipe differ
AttributeOpenSearchSteampipe
Pricing modelOpen source, no licence fee; managed services billed separatelyOpen source, with paid hosting through Turbot Pipes
PlatformsLinux, Docker, Kubernetes, Self-hostedmacOS, Linux, Windows, Docker, Web
CategoryDatabasesDeveloper Tools

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 OpenSearch

  • Full-text search
  • OpenSearch Dashboards
  • Log analytics
  • Vector search

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.

OpenSearch

  • Log and observability storage where an Apache-2.0 licence is a requirementnot Steampipe
  • Replacing Elasticsearch after the licence change without changing architecturenot Steampipe
  • Search plus analytics on one cluster rather than two systemsnot Steampipe

Steampipe

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

Where each one falls short

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

OpenSearch

  • Diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • Operationally heavy in the way Elasticsearch is: cluster sizing, shard strategy and JVM tuning are ongoing work
  • Smaller ecosystem of third-party tooling than Elasticsearch, which most integrations still target first
  • Overkill for plain application search, where a dedicated search engine is far simpler

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

OpenSearch

Free
  • OpenSearchFree
    • Full functionality
    • Self-hosted
    • No usage limits

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 OpenSearch if

  • You need full-text search.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want opensearch dashboards.
OpenSearch 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 OpenSearch or Steampipe better?
Neither clearly leads. OpenSearch 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, OpenSearch or Steampipe?
OpenSearch starts at Free and Steampipe at Free.
Does OpenSearch or Steampipe run on more platforms?
OpenSearch runs on Linux, Docker, Kubernetes, Self-hosted. Steampipe runs on macOS, Linux, Windows, Docker, Web.
Can I use OpenSearch for free?
Both have a free tier, so you can try either at no cost before committing.
What is OpenSearch best used for?
OpenSearch is most often used for log and observability storage where an apache-2.0 licence is a requirement, replacing elasticsearch after the licence change without changing architecture, search plus analytics on one cluster rather than two systems. Of those, log and observability storage where an apache-2.0 licence is a requirement and replacing elasticsearch after the licence change without changing architecture are not what Steampipe is typically brought in for.
What can OpenSearch do that Steampipe cannot?
OpenSearch covers Full-text search, OpenSearch Dashboards, Log analytics, Vector search. Steampipe covers SQL over live APIs, Wide plugin set, Embedded Postgres, Compliance benchmarks.

Answered from the vendors’ own pages

OpenSearch: Is OpenSearch free?

Yes, Apache 2.0 licensed under the Linux Foundation. Amazon OpenSearch Service is a paid managed option.

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.

OpenSearch: Why does OpenSearch exist?

Elastic moved Elasticsearch off the Apache 2.0 licence in 2021. AWS forked the last Apache-licensed version, and the project now sits under the Linux Foundation.

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.

OpenSearch: Is OpenSearch compatible with Elasticsearch?

It was at the 7.10 fork point. Both have developed independently since, so compatibility weakens with every release and should be verified for the features you use.

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.

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.

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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