KNIME: Great value, great compatibility
Christopher Penn | TrustRadius Reviewer
June 29, 2020

KNIME: Great value, great compatibility

Score 7 out of 10
Vetted Review
Verified User
Review Source

Overall Satisfaction with KNIME Analytics Platform

KNIME is used as a bridge piece of software that connects multiple, disparate data sources into a single data pipeline for further analysis downstream. Some level of transformation is done in the processing, mainly for data cleansing, but most of that is left to custom code further on in the pipeline.
  • Connection to multiple data sources.
  • Unified interface for data and cleansing.
  • Cross platform interoperability.
  • Cumbersome UI.
  • Slow to load.
  • Memory/CPU hog.
  • Positive ROI due to low cost.
  • Cross platform meant others could interchange models.
  • Available help was beneficial.
KNIME is a lower price point and has strong cross platform capabilities. Other platforms are locked to a specific operating system and cost in some cases substantially more, making them less good choices for smaller businesses that still need basic data unification. The fact that KNIME is OS-independent is a big positive.
Good support from the user community, including recipes and templates.

Do you think KNIME Analytics Platform delivers good value for the price?

Yes

Are you happy with KNIME Analytics Platform's feature set?

Yes

Did KNIME Analytics Platform live up to sales and marketing promises?

Yes

Did implementation of KNIME Analytics Platform go as expected?

Yes

Would you buy KNIME Analytics Platform again?

No

KNIME is well suited for the data analyst that has multiple disparate data sources and needs to unify them, with a price point that is lower than some other enterprise packages. It's less well suited for smaller data pipelines or pipelines where a ton of custom coding and modification needs to be made.

KNIME Analytics Platform Feature Ratings

Connect to Multiple Data Sources
10
Extend Existing Data Sources
6
Automatic Data Format Detection
7
MDM Integration
6
Visualization
3
Interactive Data Analysis
4
Interactive Data Cleaning and Enrichment
6
Data Transformations
5
Data Encryption
2
Built-in Processors
5
Multiple Model Development Languages and Tools
5
Automated Machine Learning
2
Single platform for multiple model development
4
Self-Service Model Delivery
3
Flexible Model Publishing Options
6
Security, Governance, and Cost Controls
5