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Databases · head to head

Apache Druid vs Sigma Computing

Apache Druid logo

Apache Druid

Databases

Real-time analytics database for sub-second OLAP queries

From
Free
Rated
-
Full reviewWebsite
Sigma Computing logo

Sigma Computing

Spreadsheets

Spreadsheet-style analytics that queries a cloud data warehouse directly with no extract layer

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Apache Druid has a free tier, so it costs nothing to try first.
  • Each has a real cost: Apache Druid open-source offering lacks high-availability, distributed architecture, and enterprise security features; Sigma Computing every user interaction is a live warehouse query, so compute costs rise with adoption and land on the warehouse invoice rather than the BI line item, which routinely surprises the team that approved the purchase.
  • They diverge on capability: Apache Druid covers Real-time Ingestion, Sigma Computing covers Spreadsheet interface over SQL.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Apache Druid and Sigma Computing actually diverge.

Attributes where Apache Druid and Sigma Computing differ
AttributeApache DruidSigma Computing
Starting priceFreeOn request
Pricing modelopen-sourcequote
Free tierYesNo
PlatformsDocker, Kubernetes, Native deployment (Java-based)Web
CategoryDatabasesSpreadsheets
Founded1999Unknown

Identical on both: 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 Druid

  • Real-time Ingestion
  • Sub-second Queries
  • Column-oriented Storage
  • Streaming Integration
  • Approximate Algorithms
  • Flexible Schemas
  • Time-based Partitioning
  • Kafka

Only in Sigma Computing

  • Spreadsheet interface over SQL
  • No extract layer
  • Input tables and write-back
  • Workbooks
  • Embedded analytics
  • Version control and dbt awareness

What people use each for

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

Apache Druid

  • Real-time analytics platforms ingesting millions of events per second from streaming sourcesnot Sigma Computing
  • Applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows)not Sigma Computing
  • Time-series and event analysis at massive scale with columnar storage efficiencynot Sigma Computing

Sigma Computing

  • A finance or operations team that lives in spreadsheets and needs warehouse-scale data without exporting CSVsnot Apache Druid
  • An organisation that has consolidated on Snowflake or Databricks and wants one governed access layer rather than several desktop toolsnot Apache Druid
  • Planning and scenario work where users need to type assumptions back into governed tables rather than into a local filenot Apache Druid
  • Embedding customer-facing analytics into a product where each tenant must only see their own rowsnot Apache Druid

Where each one falls short

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

Apache Druid

  • Open-source offering lacks high-availability, distributed architecture, and enterprise security features
  • Requires native integration with Apache Kafka or Amazon Kinesis for real-time ingestion; custom integrations need development
  • High-concurrency query support (hundreds of thousands QPS) requires significant cluster infrastructure investment

Sigma Computing

  • Every user interaction is a live warehouse query, so compute costs rise with adoption and land on the warehouse invoice rather than the BI line item, which routinely surprises the team that approved the purchase.
  • It cannot work without a supported cloud data warehouse, so an organisation running analytics on an on-premises database or a plain application database has nothing to connect to.
  • Pricing is not published and seats are differentiated by capability, so budgeting requires a sales cycle and a headcount forecast before you can compare it with a tool you could simply buy.
  • Performance is only as good as the warehouse behind it, which means slow or badly modelled tables surface as a slow interface and the fix is a data engineering project, not a Sigma setting.
  • Statistical and scientific visualisation is limited compared with dedicated tools, so anything beyond standard business charting has to be done elsewhere and brought back in.

Pricing, plan by plan

Apache Druid

Free

No published plan breakdown. See the Apache Druid review.

Sigma Computing

On request
  • Sigma Computing$undefined/year
    • Quoted per organisation
    • Seat types are differentiated by whether a user views, explores or authors
    • Warehouse compute is billed separately by your cloud data warehouse vendor

Which should you pick?

Choose Apache Druid if

  • You need real-time ingestion.
  • You want to start without paying.
  • You work on Docker, Kubernetes, Native deployment (Java-based).
  • You also want sub-second queries.
Apache Druid review

Choose Sigma Computing if

  • You need spreadsheet interface over sql.
  • You also want no extract layer.
Sigma Computing review

Questions people ask

Is Apache Druid or Sigma Computing better?
Neither clearly leads. Apache Druid starts at Free and Sigma Computing at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Druid or Sigma Computing?
Apache Druid has a free tier; the other does not. Paid plans start at Free for Apache Druid and On request for Sigma Computing.
Does Apache Druid or Sigma Computing run on more platforms?
Apache Druid runs on Docker, Kubernetes, Native deployment (Java-based). Sigma Computing runs on Web.
Can I use Apache Druid for free?
Yes. Apache Druid has a free tier, so you can try it without paying. Sigma Computing starts at On request.
What is Apache Druid best used for?
Apache Druid is most often used for real-time analytics platforms ingesting millions of events per second from streaming sources, applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows), time-series and event analysis at massive scale with columnar storage efficiency. Of those, real-time analytics platforms ingesting millions of events per second from streaming sources and applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows) are not what Sigma Computing is typically brought in for.
What can Apache Druid do that Sigma Computing cannot?
Apache Druid covers Real-time Ingestion, Sub-second Queries, Column-oriented Storage, Streaming Integration. Sigma Computing covers Spreadsheet interface over SQL, No extract layer, Input tables and write-back, Workbooks.

Answered from the vendors’ own pages

Apache Druid: Is Apache Druid free to use?

Apache Druid is an open-source project with no licensing fees. It is licensed under CC BY-SA 4.0, and the Druid name and logo are trademarks of The Apache Software Foundation.

Source
Sigma Computing: Does Sigma store a copy of my data?

No. Queries are executed on your warehouse and results are returned for display, which is why there is no extract refresh to manage.

Apache Druid: Can I use Apache Druid for commercial purposes?

Yes, Apache Druid is open-source software available for commercial use at no cost. The CC BY-SA 4.0 license permits commercial deployment.

Source
Sigma Computing: What does it actually cost?

The vendor does not publish prices. Expect an annual contract priced by seat type, plus a warehouse compute increase you should model separately.

Apache Druid: Where do I find pricing for commercial support or services?

No pricing or support tiers are published on the Apache Druid homepage. For commercial support options, contact the Apache Druid community or consult additional resources beyond the project website.

Source
Sigma Computing: Can business users break the warehouse?

They can run expensive queries. Warehouse sizing, query limits and materialised tables are the controls, and they need configuring before a wide rollout.

Sigma Computing: Is it a replacement for a modelling layer like dbt?

No. Sigma works best on top of modelled tables and is usually deployed alongside dbt rather than instead of it.

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