Amundsen vs. Causal

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amundsen
Score 0.0 out of 10
N/A
An open-source data discovery & metadata engine, created at Lyft, and available free under an Apache 2.0 license. Amundsen aims to boost the productivity of data analysts, data scientists and engineers when interacting with data, by indexing data resources (tables, dashboards, streams, etc.) and powering a page-rank style search based on usage patterns (e.g. highly queried tables show up earlier than less queried tables). The project is named after Norwegian explorer Roald Amundsen, the first…
$0
Causal
Score 10.0 out of 10
N/A
Causal, from the company of the same name in London, presents a way to perform calculations, visualise data, and communicate with numbers. It helps build models faster, connect them directly to data, and share them with interactive dashboards and visuals. Suggested use cases are financial planning, planning CPC campaigns, track KPIs, or determine employee compensation.
$50
per month
Pricing
AmundsenCausal
Editions & Modules
No answers on this topic
Pro
$50
per user, per month
Business
Contact Sales
Offerings
Pricing Offerings
AmundsenCausal
Free Trial
NoYes
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Features
AmundsenCausal
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Amundsen
-
Ratings
Causal
9.3
1 Ratings
14% above category average
Pixel Perfect reports00 Ratings8.01 Ratings
Customizable dashboards00 Ratings10.01 Ratings
Report Formatting Templates00 Ratings10.01 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Amundsen
-
Ratings
Causal
8.3
1 Ratings
6% above category average
Drill-down analysis00 Ratings9.01 Ratings
Formatting capabilities00 Ratings8.01 Ratings
Report sharing and collaboration00 Ratings8.01 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Amundsen
-
Ratings
Causal
8.0
1 Ratings
2% below category average
Publish to Web00 Ratings8.01 Ratings
Publish to PDF00 Ratings8.01 Ratings
Report Versioning00 Ratings8.01 Ratings
Report Delivery Scheduling00 Ratings8.01 Ratings
Delivery to Remote Servers00 Ratings8.01 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Amundsen
-
Ratings
Causal
8.0
1 Ratings
3% above category average
Predictive Analytics00 Ratings8.01 Ratings
Pattern Recognition and Data Mining00 Ratings8.01 Ratings
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User Ratings
AmundsenCausal
Likelihood to Recommend
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
AmundsenCausal
Likelihood to Recommend
Open Source
No answers on this topic
Causal, Inc
Definitely suited best for B2B / B2B2C product modelling. We used this for B2B / B2B2C / C2C and the C2C side of things was always more complex to model out due to this being dependent on marketing spend (CAC) and factors around virality which really cannot be forecasted (not a shortcoming of Causal, just implied by the mechanics of modelling)
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