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ClickHouse vs Pulumi

ClickHouse logo

ClickHouse

Software

Fast open-source column-oriented database for real-time analytics

From
Free
Rated
-
Full reviewWebsite
Pulumi logo

Pulumi

Software

Modern infrastructure as code using programming languages

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: ClickHouse limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems; Pulumi the free Individual plan allows one user and one concurrent stack update
  • They diverge on capability: ClickHouse covers Column-oriented Storage, Pulumi covers Multi-language support.

Where they differ

Only the attributes on which ClickHouse and Pulumi actually diverge.

Attributes where ClickHouse and Pulumi differ
AttributeClickHousePulumi
Pricing modelUnknownfreemium
PlatformsLinux, macOS, Windows (via Docker)Linux, Windows, Mac, Api
Founded20212017

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).

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 ClickHouse

  • Column-oriented Storage
  • Real-time Analytics
  • SQL Support
  • Linear Scalability
  • Data Compression
  • Vectorized Query Execution
  • Approximate Calculations
  • Kafka

Only in Pulumi

  • Multi-language support
  • Multi-cloud
  • State management
  • Secrets management
  • RBAC
  • Stacks
  • Automation API
  • Policy as Code

Both cover

  • Linux support

What people use each for

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

ClickHouse

  • Business intelligencenot Pulumi
  • Data warehousingnot Pulumi
  • Real-time analyticsnot Pulumi
  • Reportingnot Pulumi
  • Machine learningnot Pulumi

Pulumi

  • Defining cloud infrastructure as code in TypeScript, Python, Go, C# or Java rather than a DSLnot ClickHouse
  • Managing Pulumi state and secrets in a hosted backend instead of self-managed storagenot ClickHouse
  • Policy, drift detection and deployment workflows for platform engineering teamsnot ClickHouse

Where each one falls short

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

ClickHouse

  • Limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems
  • Requires upfront schema design discipline with MergeTree engine choices and sort/partition keys
  • Experimental vector search support, not production-ready for vector operations
  • Different query syntax from standard SQL requiring migration planning
  • Limited JOIN capabilities compared to traditional relational databases
  • Migration complexity with 2-4 weeks estimated for data type mapping and query translation

Pulumi

  • The free Individual plan allows one user and one concurrent stack update
  • The Team plan is $40 per month base including 40 credits, and caps the organisation at 10 users
  • SAML/SSO, RBAC, audit logs and drift detection require the Enterprise plan at $400 per month base
  • The per-resource rate rises from $0.1825 per resource per month on Team to $0.365 on Enterprise, so upgrading raises the unit price as well as the base fee
  • Managed secrets are billed separately at $0.50 per secret per month on Team and $0.75 on Enterprise
  • Self-hosting, SCIM user sync, audit log export and 24x7 support are only in Business Critical, which is custom priced with no published rate
  • Team includes up to 500 resources and Enterprise up to 2,000, with everything beyond billed on demand as credits

Pricing, plan by plan

ClickHouse

Free

No published plan breakdown. See the ClickHouse review.

Pulumi

Free
  • Pulumi CommunityFree
    • Open source
    • Community support
    • Self-hosted
  • Pulumi Cloud$10/month
    • Hosted backend
    • Team collaboration
    • RBAC

Which should you pick?

Choose ClickHouse if

  • You need column-oriented storage.
  • You want to start without paying.
  • You work on Linux, macOS, Windows (via Docker).
  • You also want real-time analytics.
ClickHouse review

Choose Pulumi if

  • You need multi-language support.
  • You want to start without paying.
  • You work on Linux, Windows, Mac, Api.
  • You also want multi-cloud.
Pulumi review

Questions people ask

Is ClickHouse or Pulumi better?
Neither clearly leads. ClickHouse starts at Free and Pulumi at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClickHouse or Pulumi?
ClickHouse starts at Free and Pulumi at Free.
Does ClickHouse or Pulumi run on more platforms?
ClickHouse runs on Linux, macOS, Windows (via Docker). Pulumi runs on Linux, Windows, Mac, Api.
Can I use ClickHouse for free?
Both have a free tier, so you can try either at no cost before committing.
What is ClickHouse best used for?
ClickHouse is most often used for business intelligence, data warehousing, real-time analytics, reporting. Of those, business intelligence and data warehousing are not what Pulumi is typically brought in for.
What can ClickHouse do that Pulumi cannot?
ClickHouse covers Column-oriented Storage, Real-time Analytics, SQL Support, Linear Scalability. Pulumi covers Multi-language support, Multi-cloud, State management, Secrets management. Both handle Linux support.

Answered from the vendors’ own pages

ClickHouse: What is ClickHouse best used for?

ClickHouse is optimized for analytical workloads on large datasets. It excels at fast aggregations and queries, being 10-100x faster than PostgreSQL on large aggregations.

Source
ClickHouse: Does ClickHouse support transactions?

ClickHouse has limited transaction support and expensive UPDATE/DELETE operations. It is not suitable for transactional workloads requiring strict ACID guarantees.

Source
ClickHouse: How does ClickHouse compare to PostgreSQL?

ClickHouse is 10-100x faster for analytics but PostgreSQL is better for transactional workloads. Many teams use both: PostgreSQL for writes via MaterializedPostgreSQL replication to ClickHouse for analytics.

Source
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Related pages

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