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Databases · head to head

Apache Kafka vs Steampipe

Apache Kafka logo

Apache Kafka

Databases

Open-source distributed event streaming platform

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: Apache Kafka operationally heavy to self-host: brokers, storage, rebalancing and upgrades are a standing job, which is why managed Kafka is a large market; 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: Apache Kafka covers Durable commit log, 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 Apache Kafka and Steampipe actually diverge.

Attributes where Apache Kafka and Steampipe differ
AttributeApache KafkaSteampipe
Pricing modelOpen source, no licence fee; managed services billed separatelyOpen source, with paid hosting through Turbot Pipes
PlatformsLinux, Windows, macOS, Self-hosted, DockermacOS, 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 Apache Kafka

  • Durable commit log
  • Horizontal scale
  • Kafka Connect
  • Kafka Streams
  • Replication
  • Low latency

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.

Apache Kafka

  • Moving events between services without point-to-point couplingnot Steampipe
  • Feeding analytics and warehouses from operational systems in near real timenot Steampipe
  • Replaying history to rebuild state after a consumer bugnot Steampipe
  • Buffering bursty producers ahead of slower downstream systemsnot Steampipe

Steampipe

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

Where each one falls short

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

Apache Kafka

  • Operationally heavy to self-host: brokers, storage, rebalancing and upgrades are a standing job, which is why managed Kafka is a large market
  • Overkill for straightforward job queues, where a simpler broker is easier to run and reason about
  • Ordering guarantees hold per partition, not per topic, and getting partitioning wrong is a common and expensive design mistake
  • The ecosystem is fragmented across the Apache project and vendor distributions, so documentation and tooling advice often assume a particular distribution

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

Apache Kafka

Free
  • Apache KafkaFree
    • Full platform
    • Kafka Connect
    • Kafka Streams

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 Apache Kafka if

  • You need durable commit log.
  • You want to start without paying.
  • You work on Linux, Windows, macOS, Self-hosted, Docker.
  • You also want horizontal scale.
Apache Kafka 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 Apache Kafka or Steampipe better?
Neither clearly leads. Apache Kafka 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, Apache Kafka or Steampipe?
Apache Kafka starts at Free and Steampipe at Free.
Does Apache Kafka or Steampipe run on more platforms?
Apache Kafka runs on Linux, Windows, macOS, Self-hosted, Docker. Steampipe runs on macOS, Linux, Windows, Docker, Web.
Can I use Apache Kafka for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Kafka best used for?
Apache Kafka is most often used for moving events between services without point-to-point coupling, feeding analytics and warehouses from operational systems in near real time, replaying history to rebuild state after a consumer bug, buffering bursty producers ahead of slower downstream systems. Of those, moving events between services without point-to-point coupling and feeding analytics and warehouses from operational systems in near real time are not what Steampipe is typically brought in for.
What can Apache Kafka do that Steampipe cannot?
Apache Kafka covers Durable commit log, Horizontal scale, Kafka Connect, Kafka Streams. Steampipe covers SQL over live APIs, Wide plugin set, Embedded Postgres, Compliance benchmarks.

Answered from the vendors’ own pages

Apache Kafka: Is Apache Kafka free?

Yes. Kafka is open source under the Apache License v2 with no licence fee. Costs come from the infrastructure you run it on, or from a managed service such as Confluent Cloud.

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.

Apache Kafka: How is Kafka different from a message queue?

A queue usually removes a message once it is consumed. Kafka keeps an ordered, durable log, so consumers track their own position and history can be replayed — which is what makes rebuilding state after a bug possible.

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.

Apache Kafka: Who uses Kafka?

The project reports use by more than 80% of the Fortune 100, with over 5 million lifetime downloads.

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.

Apache Kafka: Do I need to run Kafka myself?

No. Self-hosting is the operationally expensive option; managed services such as Confluent Cloud run the brokers for you and bill on throughput and storage instead.

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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