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KubitWarehouse-Native Customer Journey Analytics—No Black Boxes. Total Transparency. Kubit is the leading customer journey analytics platform, purpose-built for product, data, and marketing teams that need self-service insights, real-time data visibility, and complete control—without engineering bottlenecks or vendor lock-in. Unlike legacy analytics solutions, Kubit is natively integrated with your cloud data warehouse (Snowflake, BigQuery, Databricks), so you can analyze customer behavior and user journeys directly at the source. No data exports. No hidden models. No black-box limitations. With out-of-the-box capabilities for funnel analysis, retention metrics, user pathing, and cohort analysis, Kubit delivers actionable insights across the full customer lifecycle. Layer in real-time anomaly detection and exploratory analytics to move faster, optimize performance, and drive user engagement. Leading brands like Paramount, TelevisaUnivision, and Miro rely on Kubit for its flexibility, enterprise-grade governance, and best-in-class customer support. See why Kubit is redefining customer journey analytics at kubit.ai
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RaimaDBRaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
What is bipp?
Bipp has developed a cloud-based BI platform that leverages the unique bippLang data modeling language, designed specifically for SQL and data analysts right from the start. This platform boosts team productivity, empowering organizations to make faster and more informed decisions. By simplifying SQL queries, bippLang allows users to create complex, reusable data models that feature custom columns and dynamic sub-queries. The integration of Git-based version control enables collaborative efforts among analysts, ensuring that all data models and SQL queries have consistent backups. An always-free version of the platform grants users access to a powerful BI tool along with professional support at no cost. In-database analytics streamline processes by removing the necessity of transferring data elsewhere, resulting in quicker access and real-time insights. The auto-SQL generator smartly uses established joins within the data model to identify which tables to merge, dynamically crafting sub-queries based on the given context. Additionally, the unified data models provide a single source of truth, ensuring that everyone in the organization bases their decisions on the same data, which promotes reliability and consistency throughout the company. Ultimately, this holistic approach not only fosters collaboration but also lays a strong foundation for improved strategic planning and decision-making. As businesses increasingly prioritize data-driven strategies, Bipp’s platform stands out as an essential tool for the modern analyst.
What is JMP Statistical Software?
JMP, a data analysis tool available for both Mac and Windows, integrates robust statistical capabilities with engaging interactive visualizations.
Users can effortlessly import and analyze data thanks to its drag-and-drop interface, which features dynamically linked graphics, extensive libraries of advanced analytical tools, a scripting language, and various options for sharing insights, enabling a more profound exploration of data.
Founded in 1980, JMP was created to harness the emerging potential of graphical user interfaces for personal computers, and it has consistently evolved by incorporating state-of-the-art statistical techniques in each new version.
Remarkably, John Sall, the founder of JMP, remains actively involved in the development of the software as its Chief Architect, ensuring that it stays at the forefront of data analysis innovation.
Integrations Supported
Amazon Redshift
Impala
Microsoft Excel
MySQL
PostgreSQL
SQL Server
FACS
Firebird
Google Cloud Platform
IBM Db2
Integrations Supported
Amazon Redshift
Impala
Microsoft Excel
MySQL
PostgreSQL
SQL Server
FACS
Firebird
Google Cloud Platform
IBM Db2
API Availability
Has API
API Availability
Has API
Pricing Information
$10 per user per month
Free Trial Offered?
Free Version
Pricing Information
$1500.00/year/user
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
bipp analytics
Date Founded
2017
Company Location
United States
Company Website
bipp.io
Company Facts
Organization Name
JMP Statistical Software
Date Founded
1989
Company Location
United States
Company Website
www.jmp.com
Categories and Features
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Categories and Features
Dashboard
Annotations
Data Source Integrations
Functions / Calculations
Interactive
KPIs
OLAP
Private Dashboards
Public Dashboards
Scorecards
Themes
Visual Analytics
Widgets
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Qualitative Data Analysis
Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis
Statistical Analysis
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization