Backed By Mode Analytics, Inc.
Collaborative analytics and data visualization platform for data teams.
Mode is a collaborative analytics platform that combines SQL, Python, and R notebooks with powerful data visualization and dashboarding tools. It enables data teams to explore, analyze, and share insights in real time. Mode integrates with cloud data warehouses and BI tools, supporting advanced analytics, reporting, and workflow automation.
SQL, Python, and R notebooks
Share dashboards and reports
Custom charts and dashboards
Real-time data exploration
Connect to cloud data warehouses
Embed analytics in workflows
Up to 3 users
Minimum 3 users
Minimum 50 users
SQL Editor
Integrated Python and R Notebooks (Jupyter-compatible)
Visual Explorer (Drag-and-drop analytics)
Interactive Dashboards and Reports
Reusable Datasets and Governed Metrics (dbt integration)
Real user experiences from across different platforms
The best thing which I like about the Mode is that we can create visualization and reports from the result of SQL Queries. The best feature of Mode is that we can make different types of visualization in Mode itself, and we don't need any other tool for quick insights. So far, I haven't encountered any downside of Mode.
SK. Sahil K.
02/24/2023
tional drag-and-drop BI tools (e.g., Tableau, Power BI) and need a flexible, code-first approach.
advanced analytical work and executive-level dashboard reporting.
the high minimum cost of paid plans (Studio is the only free option).
-only BI solution.
Unites the flexibility and depth of code-first advanced analytics with the accessibility and governance of traditional Business Intelligence, accelerating the path from raw data to business action.
No public pricing; paid tiers are generally expensive and require annual contracts (high renewal risk). Some users find the UI/dashboard layout inflexible or clunky compared to pure visualization tools. Requires a foundational understanding of SQL or coding for core data manipulation tasks. Query execution can be slow at high data volumes (user-reported).