Sold by: ThoughtSpot
Deployed on AWS
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4.4
Overview
ThoughtSpot Analytics is an AI-native BI platform powered by a team of agents. Spotter, the agentic AI analyst, answers plain-language questions with multi-step reasoning SpotterModel builds governed semantic models from raw data in minutes. SpotterViz generates complete, story-driven Liveboards from a single prompt. SpotterCode brings AI-assisted development into the IDE. All of it runs live against your cloud data warehouse, with enterprise-grade security and row-level governance intact.
Give your cloud data platform a modern consumer front-end and deliver safe, reliable self-service analytics to all users. ThoughtSpot is compatible with Amazon Redshift, Snowflake, Databricks, Google BigQuery, Azure Synapse and more.
For custom pricing, EULA, or a private contract, please contact cloud-marketplace-orders@thoughtspot.com for a private offer.
Highlights
- Self-service analytics the way it was meant to be -ThoughtSpot Analytics empowers everyone from the C-suite to frontline teams to get immediate answers to their business questions and make fact-driven decisions.
- So much more than a dashboard - Unlike static dashboards, Liveboards provide a real-time, interactive view of your data, keeping you updated on business metrics as they evolve. Easily drill down from high-level analytics to the most granular insights without the need for pre-defining drill paths.
- An AI Analyst to deliver true self-service at scale Spotter, ThoughtSpots agentic AI analyst, delivers true self-service on your business data, backed by enterprise-grade trust. Ask any data on any question and get immediate answers in a conversational interface. Advanced semantic models and human-in-the-loop feedback make it easy to train Spotter to understand your industry and deliver precise, contextual insights you can trust.
Details
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Buyer guide
Gain valuable insights from real users who purchased this product, powered by PeerSpot.
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AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Pro | Starting at $1,250/month for 25 users. 250m rows of data. Annual Contract. | $1,250.00 |
Enterprise | Starting at $3,000/month for 30 users. Unlimited data. Annual contract | $3,000.00 |
Dimensions summary
You choose between two annual contract plans priced by user count. The Pro plan bundles a set number of users with a data cap measured in rows. The Enterprise plan bundles more users and removes the data cap, offering unlimited data. Both plans bill monthly under a yearly commitment, and each has a starting user allotment. Pricing scales with the number of users you need and whether you require a fixed row limit or unlimited data. Pick Pro for a defined data volume, or Enterprise when you need to grow data without limits.
Top-of-mind questions for buyers
Each user is one named person granted access to the platform. Pro starts at 25 users, and Enterprise starts at 30 users. Both plans set a starting user allotment, so your bill reflects the number of named accounts you provision, not the number of queries they run.
User count drives your cost. Pro bundles a fixed data cap of 250 million rows, while Enterprise removes that cap with unlimited data. Data volume does not add separate charges within a plan; you choose Enterprise when you need to grow rows beyond the Pro limit.
No. The vendor states it does not meter or charge for LLM tokens; platform use is governed by your subscription. If you connect your own LLM provider, that provider's fees may apply separately from your plan.
www.thoughtspot.com
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Updated weekly
By ThoughtSpot
By Omni Analytics
Top
10
In Analytics, Data Warehouses
Top
10
In Analytic Platforms, Data Analytics, Business Intelligence & Advanced Analytics
Top
25
In Data Governance, Business Intelligence & Advanced Analytics
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Agentic AI Analysis
Spotter agentic AI analyst answers plain-language questions with multi-step reasoning and conversational interface for self-service analytics at scale.
Automated Visualization Creation
SpotterViz generates complete, story-driven Liveboards from a single prompt with real-time, interactive data views.
Multi-Cloud Data Warehouse Compatibility
Runs live against cloud data warehouses including Amazon Redshift, Snowflake, Databricks, Google BigQuery, and Azure Synapse.
Row-Level Data Governance
Enterprise-grade security and row-level governance controls maintained across all analytics operations and self-service access.
API-First Architecture
Platform designed with API-first approach enabling seamless integration of analytics capabilities within applications
Embedded Analytics
Capability to embed in-context analytics directly within applications for action-oriented insights
AI-Powered Analytics
Analytics engine powered by artificial intelligence for generating insights and data-driven recommendations
Data Integration
Seamless integration of analytics across business systems and applications for unified data analysis
Decision Intelligence
Analytics platform designed to enhance decision-making capabilities through integrated insights and analytics
Semantic Layer Architecture
Built-in semantic model that provides governed metrics and ensures consistency across analytics queries and AI-generated answers
Conversational AI Analytics
Natural language processing capability enabling users to ask AI questions and receive trusted answers without requiring SQL knowledge
Git Integration and Version Control
Git-based integration with branching, content validation, and version history for managing changes to semantic models and analytics content
Excel Workflow Integration
Native Excel spreadsheet compatibility allowing users to perform financial modeling, forecasting, and exploratory analysis within the platform
Software Development Lifecycle Features
CICD pipeline support, content validation, and developer workflows for safely testing and deploying model changes across environments
Standard contract
No
Customer reviews
Health, Wellness and Fitness
Developer-Friendly Experience with Neat API Docs and Playground
Reviewed on Oct 20, 2026
Review provided by G2
What do you like best about the product?
I love how developer friendly it is. Small things like being able to copy in markdown the api documentation, the playground, etc are really neat.
What do you dislike about the product?
It seems to be less flexible than Quicksight from where we're migrating, the capability to map a control to different filters in different answers for example is one we've had to work around because it's not possible on TS
What problems is the product solving and how is that benefiting you?
It's a BI tool, it's cheaper than QS for our use cases, it's neat and AI first.
Market Research
Easy to Use, Helpful Support, and Continual Product Improvements
Reviewed on Oct 09, 2026
Review provided by G2
What do you like best about the product?
Easy to use. Support team is always approachable and very helpful. And they keep developing their product and take customer feedback serious.
What do you dislike about the product?
Takes a bit of time to embed in the organization. Not everyone can work with it that easy. I often get errors when working on a liveboard.
What problems is the product solving and how is that benefiting you?
Creating the liveboards can now be done easier with the use of AI. For our company, insights are displayed better than our previous dashboards and it's also easier to use for our customers.
Jesus D.
Intuitive AI Search and Instant Visualizations Make Data Exploration Easy
Reviewed on Oct 06, 2026
Review provided by G2
What do you like best about the product?
What I like best about ThoughtSpot is how intuitive the UI/UX is — even non-technical users can explore data without needing to write queries. The AI/Intelligence-driven search makes it easy to ask questions in plain language and get instant visualizations. It also integrates well with our existing data sources, which made rollout across teams much smoother.
What do you dislike about the product?
What I dislike about ThoughtSpot is that performance can slow down noticeably when working with very large datasets or complex queries. The pricing/ROI is also a bit steep for smaller teams, which can make it harder to justify at scale. Additionally, support/onboarding has a learning curve — new users often need extra time and guidance to get fully up to speed.
What problems is the product solving and how is that benefiting you?
ThoughtSpot is helping us solve the problem of slow, bottlenecked reporting, instead of waiting on analysts, teams can self-serve answers directly thanks to the intuitive UI/UX and AI/Intelligence-powered search. The integrations with our existing data sources meant we didn't have to overhaul our stack to get value quickly. Performance at scale has let us analyze larger datasets without the delays we used to see, and overall the pricing/ROI has paid off by cutting down the time previously spent on manual reporting.
Xadani U.
Easy Connections Between Different Software Tools
Reviewed on Oct 06, 2026
Review provided by G2
What do you like best about the product?
It's easy to create connections between different softwares
What do you dislike about the product?
The UI may be less intuitive than others
What problems is the product solving and how is that benefiting you?
Performance, and how Databricks connects is easier
reviewer2890881
Self-service insights have reduced ad hoc reporting and empower teams with AI-driven spend analysis
Reviewed on Aug 21, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for ThoughtSpot is to enable self-reports in our company, allowing self users to produce the dashboards themselves and query our data in Snowflake with the prompting.
Our team works in the field of procurement and uses ThoughtSpot for self-service reporting, where the main source of our data is spend reporting data. Users can ask Spotter in ThoughtSpot, pin the answers to their liveboards, and create plots tailored to their category or department, which reduces the workload for our team as we don't have to answer each ad hoc request.
In addition to my main use case, we also start using ThoughtSpot for different use cases where Spotter combines various data sources and runs deep analyses such as forecasting or joining different tables by itself.
What is most valuable?
One of the best features ThoughtSpot offers is Spotter, which gives the opportunity to translate prompts in natural language to SQL queries. Additionally, flexible dashboard solutions and the new feature called Spotter Viz are really helpful for business users to produce their own dashboards.
The natural language querying and flexible dashboards have reduced the number of ad hoc requests our team receives, as business users now have access to the data sources and can solve their ad hoc requests by directly asking ThoughtSpot.
ThoughtSpot has positively impacted my organization, being considered a successful user story and an innovative tool in our department that fosters AI development.
ThoughtSpot has helped my team by reducing the workload of each of our team members by 4-8 hours per week, which we no longer have to spend on ad hoc requests.
What needs improvement?
Currently, we notice a bug in ThoughtSpot when Spotter joins different data sets extracted from Snowflake or produced by SQL. It joins data using Python and operates only on a sample of data, so not the full dataset is analyzed by Spotter, and in our use case, only 10% of our data is correctly analyzed.
The AI model used by Spotter can still hallucinate and sometimes fails to follow the instructions precisely, even though instructions are set, which is a needed improvement.
I choose eight out of ten because the tool is very innovative and provides the opportunity to use AI to communicate with data in cloud databases. It is quite easy for business users to use, but there is still room for improvement, such as resolving the existing bugs that analyze only a sample or a fraction of the data.
The AI capabilities of Spotter can still produce hallucinations, and sometimes it analyzes only a sample of data rather than the complete dataset. These are the biggest disadvantages for my team.
For how long have I used the solution?
I have been using ThoughtSpot for the last nine months.
What do I think about the stability of the solution?
ThoughtSpot is stable most of the time we use it.
What do I think about the scalability of the solution?
ThoughtSpot's scalability is quite good, as it is easy to implement a lot of data and connect it to Snowflake. However, as I mentioned, it analyzes some data only on a sample basis, which means it cannot analyze the full dataset that it has access to.
How are customer service and support?
The customer support from ThoughtSpot is great; we receive a lot of assistance from ThoughtSpot managers, and the regular meetings we have are helpful for our ThoughtSpot adoption in the company.
Which solution did I use previously and why did I switch?
We previously used Tableau for dashboarding extensively. We did not switch completely to ThoughtSpot, as it provides opportunities to create more flexible and ad hoc solutions for our business users, while Tableau is used to produce standard reports.
What was our ROI?
ThoughtSpot was deployed in my team three months ago, so we can only determine how much time we save per week, which is about 4-8 hours per employee.
What's my experience with pricing, setup cost, and licensing?
In my large company, I did not have to deal with any pricing or setup costs. ThoughtSpot is a globally approved tool for my company, so users do not have to pay anything extra; pricing is based on the number of rows extracted for our data, which I find quite fair, with no additional costs for queries or prompts produced by users.
Which other solutions did I evaluate?
We did not evaluate any other options before choosing ThoughtSpot.
What other advice do I have?
ThoughtSpot is deployed in our organization with a server, but I am not certain of the exact technical implementation, as several organizations within the company use different instances.
ThoughtSpot provides one of the best AI capabilities available in the market for dashboard and front-end solutions. It is easy to learn to use for both technical and non-technical users and integrates well with existing data if it is already in good shape. Additionally, ThoughtSpot continues to deliver a lot of elaborated AI features to assist our users.
I rate this review eight out of ten.