Machine Learning · head to head
IBM SPSS vs Weaviate

IBM SPSS
Machine Learning
Statistical analysis software for data science
- From
- Free
- Rated
- -
The short version
- Each has a real cost: IBM SPSS add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
- They diverge on capability: IBM SPSS covers Statistical analysis, Weaviate covers Vector and keyword search.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which IBM SPSS and Weaviate actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).
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 IBM SPSS
- Statistical analysis
- Predictive modeling
- Data visualization
- Survey analysis
- Decision trees
- Python
- R
- Excel
Only in Weaviate
- Vector and keyword search
- Built-in vectorizers
- GraphQL API
- Multi-tenancy
- Hybrid search
- OpenAI
- Hugging Face
- Cohere
Both cover
- Linux support
- Mac support
- Windows support
What people use each for
The jobs each tool is most often brought in to do.
IBM SPSS
- Statistical testing and regression analysis for academic and market researchnot Weaviate
- Predictive modelling and forecasting without writing codenot Weaviate
Weaviate
- Running a vector database for semantic and hybrid searchnot IBM SPSS
- Generating and storing embeddings alongside the objects they describenot IBM SPSS
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
IBM SPSS
- Add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals
- Subscription cost renews at the then current price at the end of the first year, so the advertised rate applies to the first term only
- Prices shown are described by IBM as indicative, vary by country and exclude applicable taxes and duties
- Extended access periods of 12 months or more are handled as tailored pricing rather than a published rate
- Advanced statistics, custom tables, decision trees and forecasting are separate add-ons rather than part of the base product
Weaviate
- The free tier caps at 100,000 objects, 1 GB of memory and a single collection
- Billing is per million vector dimensions rather than per record, so wider embeddings cost proportionally more for the same object count
- Premium is a prepaid contract starting at $400 a month rather than pay as you go
- Storage rates do not fall consistently with tier, and Premium Dedicated is $0.1505 per GiB against $0.12 on the cheaper Flex plan
- The Query Agent is metered separately, free to 1,000 requests a month and $30 a month plus overage beyond
Pricing, plan by plan
IBM SPSS
Free- TrialFree
- 14-day trial
- Full features
- Base$99/month
- Core statistics
- Data management
Weaviate
Free- Open SourceFree
- Full features
- Self-hosted
- ServerlessFree
- Managed service
- Auto-scaling
Which should you pick?
Choose IBM SPSS if
- You need statistical analysis.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want predictive modeling.
Choose Weaviate if
- You need vector and keyword search.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want built-in vectorizers.
Questions people ask
- Is IBM SPSS or Weaviate better?
- Neither clearly leads. IBM SPSS starts at Free and Weaviate at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, IBM SPSS or Weaviate?
- IBM SPSS starts at Free and Weaviate at Free.
- Does IBM SPSS or Weaviate run on more platforms?
- IBM SPSS runs on Linux, Mac, Windows. Weaviate runs on Linux, Mac, Windows, Web.
- Can I use IBM SPSS for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is IBM SPSS best used for?
- IBM SPSS is most often used for statistical testing and regression analysis for academic and market research, predictive modelling and forecasting without writing code. Of those, statistical testing and regression analysis for academic and market research and predictive modelling and forecasting without writing code are not what Weaviate is typically brought in for.
- What can IBM SPSS do that Weaviate cannot?
- IBM SPSS covers Statistical analysis, Predictive modeling, Data visualization, Survey analysis. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. Both handle Linux support, Mac support, Windows support.
Answered from the vendors’ own pages
Weaviate: What pricing options does Weaviate offer?
Weaviate provides a free tier with usage-based pricing, plus enterprise options. Visit the pricing page for detailed information on plans.
SourceWeaviate: Does Weaviate offer customer support?
Yes, support is included with Weaviate's cloud offerings. Enterprise customers receive first-class support from their global team of experts.
SourceWeaviate: Can I deploy Weaviate on my own infrastructure?
Yes. Weaviate is open source and deployment-agnostic. You can run it in your own cloud environment or use their managed cloud service.
SourceWeaviate: What data security features does Weaviate provide?
Weaviate includes security & governance, RBAC, SOC 2 and HIPAA compliance, along with multi-tenancy and high availability for enterprise requirements.
SourceWeaviate: How do I get started with Weaviate?
Sign up for their cloud tier, create your first dataset, connect an LLM, and build your AI app. Documentation and quickstart guides are available for Python, Go, TypeScript, and JavaScript.
SourceRelated pages
Other head to heads
- IBM SPSS vs Azure Machine Learning
- IBM SPSS vs DataRobot
- IBM SPSS vs AWS SageMaker
- IBM SPSS vs Google Vertex AI
- IBM SPSS vs SAS
- IBM SPSS vs Stata
- IBM SPSS vs Palantir Foundry
- IBM SPSS vs Alteryx
- IBM SPSS vs Snowflake
- IBM SPSS vs Databricks
- IBM SPSS vs Dataiku
- IBM SPSS vs RapidMiner
- IBM SPSS vs Ray
- IBM SPSS vs Seldon
- IBM SPSS vs TensorBoard
- IBM SPSS vs Amazon Redshift ML
- IBM SPSS vs JMP
- IBM SPSS vs Milvus
- IBM SPSS vs Pinecone
- IBM SPSS vs Jupyter
- IBM SPSS vs Cohere
- IBM SPSS vs Ollama
- IBM SPSS vs OpenRouter
- IBM SPSS vs Orange
- IBM SPSS vs Pachyderm
- IBM SPSS vs BigQuery ML
- IBM SPSS vs Semantic Kernel
- Weaviate vs Azure Machine Learning
- Weaviate vs DataRobot
- Weaviate vs AWS SageMaker
- Weaviate vs Google Vertex AI
- Weaviate vs SAS
- Weaviate vs Stata
- Weaviate vs Palantir Foundry
- Weaviate vs Alteryx
- Weaviate vs Snowflake
- Weaviate vs Databricks
- Weaviate vs Dataiku
- Weaviate vs RapidMiner
- Weaviate vs Ray
- Weaviate vs Seldon
- Weaviate vs TensorBoard
- Weaviate vs Amazon Redshift ML
- Weaviate vs JMP
- Weaviate vs Milvus
- Weaviate vs Pinecone
- Weaviate vs Jupyter
- Weaviate vs Cohere
- Weaviate vs Ollama
- Weaviate vs OpenRouter
- Weaviate vs Orange
- Weaviate vs Pachyderm
- Weaviate vs BigQuery ML
- Weaviate vs Semantic Kernel

