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Provides a familiar spreadsheet UI on live warehouse data, improving time to value for developers and adoption for business users.
No traditional spreadsheet interface; relies on search and AI-driven analytics.
Natively queries Snowflake Semantic Views and other governed metrics without duplicating data.
Relies on modeled Worksheets; no native semantic-layer integration.
Build full, no-code Data Apps with writeback, actions, and role-based workflows directly on the warehouse.
Focused on analytics and Liveboards; no native app-building or workflow automation.
Switch between spreadsheets, SQL, Python, and AI in a single workbook without context-switching.
SQL and Python available only in separate Notebook workflows; no unified environment.
Input Tables and CSV uploads write back securely to the warehouse for planning and workflows.
No native writeback; must update data outside the platform.
Use Snowflake Cortex, Databricks Model Serving, or your own hosted LLMs for NL query and enrichment.
Tied to vendor-provided AI models only.
Query PDFs, images, and semi-structured data with File Columns + AI SQL directly in the UI.
Primarily built for structured/tabular data.
Real-time multi-user editing with role-based locks, change tracking, commenting, and shared views.
Collaboration via comments and shared views; no simultaneous co-authoring.
Define scheduled or on-demand materialization to optimize cost and performance.
Relies solely on warehouse performance; no in-tool materialization control.
Detailed lineage views for every element, tracing data origin and transformations.
Basic lineage via governed data models; lacks element-level detail.
No-code UI theming and secure iFrame embedding with signed URLs; go live in days without heavy modeling.
Requires Worksheet modeling and Visual Embed SDK setup before embedding.
Flexible switching between spreadsheet, SQL, and Python reduces brittle modeling and handoffs.
Ongoing model management needed as requirements evolve.
Full API control for provisioning users, managing permissions, and embedding governed content.
Embedding APIs exist, but governance is primarily managed manually in the UI.
Embed full Data Apps with writeback and role-based workflows for customer-facing use cases.
Embedding limited to search, Liveboards, and dashboards—no app workflows.
Optional caching and materialization to control cost/performance for embedded experiences.
No embedded materialization controls; relies on warehouse performance.
Familiar spreadsheet interface for embedded users, lowering training friction.
Requires training on search phrasing and model structure before users can explore.
Row-, column-, and cell-level security on both read and writeback actions.
Row- and column-level security for reads; no native writeback.
Bring your own AI models into embedded workflows for NLQ, enrichment, and automation.
Limited to ThoughtSpot AI capabilities in embedded contexts.
Real-time in-app support with sub-minute response times and live call scheduling.
Community-first support; in-app chat only at higher pricing tiers.
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