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Machine Learning · head to head

AWS SageMaker vs ClickHouse

AWS SageMaker logo

AWS SageMaker

Machine Learning

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite
ClickHouse logo

ClickHouse

Databases

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

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult; ClickHouse limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems
  • They diverge on capability: AWS SageMaker covers Jupyter notebooks, ClickHouse covers Column-oriented Storage.

Where they differ

Only the attributes on which AWS SageMaker and ClickHouse actually diverge.

Attributes where AWS SageMaker and ClickHouse differ
AttributeAWS SageMakerClickHouse
PlatformsWebLinux, macOS, Windows (via Docker)
CategoryMachine LearningDatabases
Founded20062021

Identical on both: starting price (Free), pricing model (Unknown), 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 AWS SageMaker

  • Jupyter notebooks
  • Built-in algorithms
  • Automatic model tuning
  • One-click deployment
  • Model monitoring
  • Lambda
  • Step Functions
  • CloudWatch

Only in ClickHouse

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

Both cover

  • S3
  • Web support

What people use each for

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

AWS SageMaker

  • Machine learning
  • Data analysisnot ClickHouse
  • Model trainingnot ClickHouse
  • Predictive analyticsnot ClickHouse

ClickHouse

  • Business intelligencenot AWS SageMaker
  • Data warehousingnot AWS SageMaker
  • Real-time analyticsnot AWS SageMaker
  • Reportingnot AWS SageMaker
  • Machine learning

Both are used for machine learning, on those jobs the choice comes down to price and fit rather than capability.

Where each one falls short

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

AWS SageMaker

  • Vendor lock-in to AWS ecosystem makes migration to other platforms difficult
  • Opaque pricing can lead to unexpected expenses like forgotten EBS volume charges
  • Does not include native job scheduling, requiring Lambda or EventBridge integration

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

Pricing, plan by plan

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

ClickHouse

Free

No published plan breakdown. See the ClickHouse review.

Which should you pick?

Choose AWS SageMaker if

  • You need jupyter notebooks.
  • You want to start without paying.
  • You also want built-in algorithms.
AWS SageMaker review

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

Questions people ask

Is AWS SageMaker or ClickHouse better?
Neither clearly leads. AWS SageMaker starts at Free and ClickHouse at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AWS SageMaker or ClickHouse?
AWS SageMaker starts at Free and ClickHouse at Free.
Does AWS SageMaker or ClickHouse run on more platforms?
AWS SageMaker runs on Web. ClickHouse runs on Linux, macOS, Windows (via Docker).
Can I use AWS SageMaker for free?
Both have a free tier, so you can try either at no cost before committing.
What is AWS SageMaker best used for?
AWS SageMaker is most often used for machine learning, data analysis, model training, predictive analytics. Of those, data analysis and model training are not what ClickHouse is typically brought in for.
What can AWS SageMaker do that ClickHouse cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. ClickHouse covers Column-oriented Storage, Real-time Analytics, SQL Support, Linear Scalability. Both handle S3, Web support.

Answered from the vendors’ own pages

AWS SageMaker: What is AWS SageMaker used for?

AWS SageMaker is a machine learning service for building, training, and deploying ML models at scale. It provides tools for data preparation, model training, inference endpoints, and performance optimization.

Source
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
AWS SageMaker: How is AWS SageMaker priced?

SageMaker uses pay-as-you-go pricing with no upfront costs or long-term commitments. Pricing starts at $0.04 per hour for basic notebook instances and scales based on instance type. ML Savings Plans offer up to 64% off with hourly spend commitments.

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
AWS SageMaker: Does AWS SageMaker have a free tier?

Yes, the free tier includes 250 hours of notebook usage, 50 hours of training, and 125 hours of hosting on ml.t3.medium instances during the first two months.

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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