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Databases · head to head

DataStax vs Semantic Kernel

DataStax logo

DataStax

Databases

The real-time data company for AI applications

From
Free
Rated
-
Full reviewWebsite
Semantic Kernel logo

Semantic Kernel

Machine Learning

Model-agnostic SDK for AI orchestration

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: DataStax dataStax's own Astra DB documentation states the Enterprise plan is an annual, contract-based plan with negotiated pricing, meaning list prices are not published for that tier; Semantic Kernel steep learning curve for advanced features
  • They diverge on capability: DataStax covers Cassandra Compatible, Semantic Kernel covers Multi-model support.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DataStax and Semantic Kernel actually diverge.

Attributes where DataStax and Semantic Kernel differ
AttributeDataStaxSemantic Kernel
Pricing modelfreemiumOpen source, no pricing
PlatformsWeb, Aws, Azure, GcpPython, .NET, Java
CategoryDatabasesMachine Learning
Founded2010Unknown

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 DataStax

  • Cassandra Compatible
  • Vector Search
  • Serverless
  • Multi-cloud
  • Streaming
  • CDC
  • GraphQL API
  • LangChain

Only in Semantic Kernel

  • Multi-model support
  • Agent framework
  • Multi-agent systems
  • Plugin ecosystem
  • Vector database integration
  • Multimodal support
  • Local model support
  • Enterprise observability

What people use each for

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

DataStax

  • Real-time applicationsnot Semantic Kernel
  • Content managementnot Semantic Kernel
  • User profilesnot Semantic Kernel
  • Mobile backendsnot Semantic Kernel
  • Cachingnot Semantic Kernel

Semantic Kernel

  • Building enterprise AI applications with LLM integrationnot DataStax
  • Creating multi-agent systems for complex workflowsnot DataStax
  • Developing AI-powered chatbots and assistantsnot DataStax
  • Implementing RAG systems with vector databasesnot DataStax

Where each one falls short

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

DataStax

  • DataStax's own Astra DB documentation states the Enterprise plan is an annual, contract-based plan with negotiated pricing, meaning list prices are not published for that tier
  • DataStax's Astra DB documentation directs Standard plan customers to IBM's watsonx.data pricing for exact consumption-based rates following the DataStax/IBM deal, rather than publishing them on DataStax's own site

Semantic Kernel

  • Steep learning curve for advanced features
  • Documentation focuses on Azure cloud services
  • Configuration complexity for multi-model scenarios
  • Requires understanding of AI/LLM concepts

Pricing, plan by plan

DataStax

Free
  • FreeFree
    • 5GB storage
    • 40M read/write ops
    • Vector search
  • Pay As You GoFree
    • Usage-based pricing
    • Multi-region
    • Enterprise support

Semantic Kernel

Free
  • Open SourceFree
    • MIT license
    • Full framework access
    • All language SDKs

Which should you pick?

Choose DataStax if

  • You need cassandra compatible.
  • You want to start without paying.
  • You work on Web, Aws, Azure, Gcp.
  • You also want vector search.
DataStax review

Choose Semantic Kernel if

  • You need multi-model support.
  • You want to start without paying.
  • You work on Python, .NET, Java.
  • You also want agent framework.
Semantic Kernel review

Questions people ask

Is DataStax or Semantic Kernel better?
Neither clearly leads. DataStax starts at Free and Semantic Kernel at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DataStax or Semantic Kernel?
DataStax starts at Free and Semantic Kernel at Free.
Does DataStax or Semantic Kernel run on more platforms?
DataStax runs on Web, Aws, Azure, Gcp. Semantic Kernel runs on Python, .NET, Java.
Can I use DataStax for free?
Both have a free tier, so you can try either at no cost before committing.
What is DataStax best used for?
DataStax is most often used for real-time applications, content management, user profiles, mobile backends. Of those, real-time applications and content management are not what Semantic Kernel is typically brought in for.
What can DataStax do that Semantic Kernel cannot?
DataStax covers Cassandra Compatible, Vector Search, Serverless, Multi-cloud. Semantic Kernel covers Multi-model support, Agent framework, Multi-agent systems, Plugin ecosystem.

Answered from the vendors’ own pages

DataStax: Is DataStax available as a managed service?

Yes, DataStax is available as Astra DB, a managed database service. Users can sign up for Astra DB directly to create accounts and access the platform.

Source
Semantic Kernel: What LLM providers does Semantic Kernel support?

Semantic Kernel supports OpenAI, Azure OpenAI, Hugging Face, Nvidia, and other providers through extensible model implementations.

Source
DataStax: How is DataStax priced?

DataStax (now part of IBM) does not publish pricing on its documentation homepage. Pricing information would need to be obtained through the Astra DB signup page or by contacting IBM directly.

Source
Semantic Kernel: Can I run Semantic Kernel locally?

Yes. Semantic Kernel supports local models through Ollama, LMStudio, and ONNX for complete data control and offline operation.

Source
DataStax: Is there an enterprise licensing option?

DataStax is now part of IBM. Enterprise customers should contact IBM directly for licensing agreements and enterprise-specific pricing.

Source
Semantic Kernel: Is Semantic Kernel free?

Yes. Semantic Kernel is MIT-licensed open source and completely free. You only pay for external LLM APIs you use.

Source
DataStax: Can I try DataStax without an account?

To use DataStax Astra DB, account creation is required. The documentation does not mention a free trial or demonstration environment that does not require signup.

Source
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