Hydrosphere Mist
Deploy Apache Spark MLlib models as real-time, batch or reactive web services.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Hydrosphere Mist?
Hydrosphere Mist is a service for deploying Apache Spark MLlib machine learning models as real-time, batch or reactive web services. It simplifies the process of serving machine learning models in production environments.
Key differentiator
“Hydrosphere Mist stands out as a specialized tool for deploying and serving Apache Spark MLlib models, offering unique capabilities in real-time and reactive web services.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development is in Scala with limited official support for other languages
GitHub activity indicates a niche user base and fewer contributors compared to more mainstream tools
Fit analysis
Who is it for?
✓ Best for
Teams needing to deploy Apache Spark MLlib models as web services in a production environment
Developers looking for real-time and reactive model serving capabilities with Apache Spark
✕ Not a fit for
Projects that do not use Apache Spark or MLlib for machine learning tasks
Applications requiring support for non-Spark-based machine learning frameworks
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Works well with
Next step
Get Started with Hydrosphere Mist
Step-by-step setup guide with code examples and common gotchas.