Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Scarf serves as a comprehensive platform aimed at delivering in-depth analytics to open-source project maintainers regarding the utilization of their software. By presenting valuable insights on aspects like the companies engaging with a project, the frequency of package downloads, and the specific versions being utilized, Scarf enhances the effectiveness of sales and marketing strategies. It plays a crucial role in discovering prospective customers within the open-source community via Open Source Qualified Leads (OQLs), thereby allowing businesses to fine-tune their outreach initiatives effectively. Additionally, Scarf's integration with multiple third-party platforms further amplifies the utility of the data it offers, ensuring that users have a holistic view of their project's impact and reach in the market. This multifaceted approach not only streamlines analytics but also fosters stronger connections between project maintainers and potential users.
Description
Rakam offers tailored reporting capabilities for various teams, ensuring that no group is confined to a single interface. It seamlessly converts the inquiries made in its user interface into SQL queries, simplifying the process for end-users. Importantly, Rakam does not transfer any data into your data warehouse; rather, it operates under the assumption that all necessary data is already stored within, allowing for analysis directly from the data warehouse, your definitive source of truth. For further insights on this subject, check out our blog post. Rakam also integrates with dbt core, serving as the data modeling layer but does not execute your dbt transformations. Instead, it connects to your GIT repository to automatically synchronize your dbt models. Additionally, Rakam can generate incremental dbt models, enhancing query performance and minimizing database costs. By defining aggregates in your dbt resource files, Rakam automatically creates roll-up models, simplifying the process for end-users while ensuring efficient data handling. This streamlined approach empowers teams to focus on insights rather than the technical intricacies of data analysis.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon Redshift
Yes
ClickHouse
Yes
Snowflake
Yes
Common Room
Yes
Domo
Yes
Firebase
No
Google Analytics 360
No
Google Cloud BigQuery
No
HubSpot CRM
Yes
HubSpot Customer Platform
Yes
Integrations
Amazon Redshift
Yes
ClickHouse
Yes
Snowflake
Yes
Common Room
No
Domo
No
Firebase
Yes
Google Analytics 360
Yes
Google Cloud BigQuery
Yes
HubSpot CRM
No
HubSpot Customer Platform
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$25 per user per month
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Scarf
Founded
2019
Country
United States
Website
about.scarf.sh/
Vendor Details
Company Name
Rakam
Founded
2016
Country
United States
Website
rakam.io
Product Features
Product Analytics
Attribution
No
Automatic Data Capture
No
Churn Reporting
No
Customer Feedback Collection
No
Customer Guidance
No
Customer Journey Analytics
No
Data Export
No
Data History Retention
No
Data Labeling
No
Product Engagement Scoring
No
Real-Time Data Analysis
No
Touchpoint Analytics
No
User Segmentation
No
Product Features
Product Analytics
Attribution
No
Automatic Data Capture
No
Churn Reporting
No
Customer Feedback Collection
No
Customer Guidance
No
Customer Journey Analytics
No
Data Export
No
Data History Retention
No
Data Labeling
No
Product Engagement Scoring
No
Real-Time Data Analysis
No
Touchpoint Analytics
No
User Segmentation
No