Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
N/A
ThoughtSpot
Score 8.5 out of 10
N/A
ThoughtSpot is an Agentic Analytics Platform for enterprises where users ask data questions using natural language and get answers with AI. Code-first for data teams and code-free for business users, ThoughtSpot can handle large, complex cloud data at scale.
$1,500
per year (5 users)
Pricing
Posit
ThoughtSpot
Editions & Modules
No answers on this topic
Thoughtspot Analytics - Pro
$50
per month (billed annually) per user (25-1000 users)
Thoughtspot Analytics - Enterprise
Custom
Offerings
Pricing Offerings
Posit
ThoughtSpot
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
Optional
Optional
Additional Details
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More Pricing Information
Community Pulse
Posit
ThoughtSpot
Features
Posit
ThoughtSpot
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Posit
9.3
27 Ratings
11% above category average
ThoughtSpot
-
Ratings
Connect to Multiple Data Sources
8.026 Ratings
00 Ratings
Extend Existing Data Sources
10.027 Ratings
00 Ratings
Automatic Data Format Detection
10.026 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Posit
9.0
27 Ratings
6% above category average
ThoughtSpot
-
Ratings
Visualization
8.027 Ratings
00 Ratings
Interactive Data Analysis
10.024 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Posit
10.0
26 Ratings
20% above category average
ThoughtSpot
-
Ratings
Interactive Data Cleaning and Enrichment
10.024 Ratings
00 Ratings
Data Transformations
10.026 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Posit
10.0
22 Ratings
17% above category average
ThoughtSpot
-
Ratings
Multiple Model Development Languages and Tools
10.022 Ratings
00 Ratings
Single platform for multiple model development
10.022 Ratings
00 Ratings
Self-Service Model Delivery
10.019 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Posit
9.9
18 Ratings
15% above category average
ThoughtSpot
-
Ratings
Flexible Model Publishing Options
10.018 Ratings
00 Ratings
Security, Governance, and Cost Controls
9.915 Ratings
00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Posit
-
Ratings
ThoughtSpot
7.3
89 Ratings
11% below category average
Pixel Perfect reports
00 Ratings
6.021 Ratings
Customizable dashboards
00 Ratings
8.289 Ratings
Report Formatting Templates
00 Ratings
7.725 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Posit
-
Ratings
ThoughtSpot
7.5
91 Ratings
7% below category average
Drill-down analysis
00 Ratings
8.590 Ratings
Formatting capabilities
00 Ratings
7.290 Ratings
Integration with R or other statistical packages
00 Ratings
5.849 Ratings
Report sharing and collaboration
00 Ratings
8.788 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Posit
-
Ratings
ThoughtSpot
8.3
84 Ratings
1% above category average
Publish to Web
00 Ratings
8.255 Ratings
Publish to PDF
00 Ratings
8.678 Ratings
Report Versioning
00 Ratings
7.918 Ratings
Report Delivery Scheduling
00 Ratings
8.464 Ratings
Delivery to Remote Servers
00 Ratings
8.135 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
In my humble opinion, if you are working on something related to Statistics, RStudio is your go-to tool. But if you are looking for something in Machine Learning, look out for Python. The beauty is that there are packages now by which you can write Python/SQL in R. Cross-platform functionality like such makes RStudio way ahead of its competition. A couple of chinks in RStudio armor are very small and can be considered as nagging just for the sake of argument. Other than completely based on programming language, I couldn't find significant drawbacks to using RStudio. It is one of the best free software available in the market at present.
It is well suited when the same data is consumed by many different people with different analytics and visualization requirements because, if you have the data available in ThoughtSpot, every user can prepare different views. Also, it is a good reporting tool, you can get rid of slides if you have a good dashboard prepared, gaining flexibility and agility.
The support is incredibly professional and helpful, and they often go out of their way to help me when something doesn't work.
The one-click publishing from RStudio Connect is absolutely amazing, and I really like the way that it deploys your exact package versions, because otherwise, you can get in a terrible mess.
Python doesn't feel quite as native as R at the moment but I have definitely deployed stuff in R and Python that works beautifully which is really nice indeed.
Beautiful visualizations. The visuals are distinct, clean, and easy to discern from one another.
Intelligent querying functionality. When looking to manipulate the data, the search function makes it easy to manipulate the features in the data, along with aggregating them in the way you'd like.
Embedding! It has been a smooth process thus far for our product & technical teams to work with ThoughtSpot and bring it into our product.
Python integration is newer and still can be rough, especially with when using virtual environments.
RStudio Connect pricing feels very department focused, not quite an enterprise perspective.
Some of the RStudio packages don't follow conventional development guidelines (API breaking changes with minor version numbers) which can make supporting larger projects over longer timeframes difficult.
It would be great if ThoughtSpot can add the feature to filter by clicking on visualizations. i.e if I click on a particular data point in the chart if the full dashboard can filter just for that particular data point.
Color coding the heatmap with different colors like green to orange to red.
There is no viable alternative right now. The toolset is good and the functionality is increasing with every release. It is backed by regular releases and ongoing development by the RStudio team. There is good engagement with RStudio directly when support is required. Also there's a strong and growing community of developers who provide additional support and sample code.
I give it just waiting because passport is brilliant and it has helped our organisation In advancing to the next stage in the age of AI. It has allowed or non-tech people to better service and clients in a cost-effective way. George port has allowed us to create new products for us and for our clients increasing our revenue streams and reducing clients churn
For someone who learns how to use the software and picks up on the "language" of R, it's very easy to use. For beginners, it can be hard and might require a course, as well as the appropriate statistical training to understand what packages to use and when
The rating is because of the ease of use of the interface as it has a no code interface that makes it easy to setup data pipelines without extensive programming. Cloud native integration: It integrates seamlessly with cloud based data warehouses. Automated data loading, Scalability, Cost Effective, Transformations, Data Governance and security.
RStudio is very available and cheap to use. It needs to be updated every once in a while, but the updates tend to be quick and they do not hinder my ability to make progress. I have not experienced any RStudio outages, and I have used the application quite a bit for a variety of statistical analyses
Since R is trendy among statisticians, you can find lots of help from the data science/ stats communities. If you need help with anything related to RStudio or R, google it or search on StackOverflow, you might easily find the solution that you are looking for.
I give it this meeting because the team is not only help able to help us in the current solutions but also amazing and taking feedback and feeding it back to their development team which includes more products and features into ThoughtSpot
RStudio was provided as the most customizable. It was also strictly the most feature-rich as far as enabling our organization to script, run, and make use of R open-source packages in our data analysis workstreams. It also provided some support for python, which was useful when we had R heavy code with some python threaded in. Overall we picked Rstudio for the features it provided for our data analysis needs and the ability to interface with our existing resources.
We also explored Tableau Ask Data. Tableau is our standard for BI in our organization. We want to use the smallest amount of tools in our company to have the best adaption. ThoughSpot will fill a few gaps that we have with our current set up and will also enhance out offering for our employees in the transition of being more data driven within in near future
RStudio is very scalable as a product. The issue I have is that it doesn't necessarily fit in nicely with the mainly Microsoft environment that everybody else is using. Having RStudio for us means dedicated servers and recruiting staff who know how to manage the environment. This isn't a fault of the product at all, it's just part of the data science landscape that we all have to put up with. Having said that RStudio is absolutely great for running on low spec servers and there are loads of options to handle concurrency, memory use, etc.
Because it is very reliable, inside the situation, we need strong internet connection to access a lot of data but easily never had any downtime except during the upgrades
Using it for data science in a very big and old company, the most positive impact, from my point of view, has been the ability of spreading data culture across the group. Shortening the path from data to value.
Still it's hard to quantify economic benefits, we are struggling and it's a great point of attention, since splitting out the contribution of the single aspects of a project (and getting the RStudio pie) is complicated.
What is sure is that, in the long run, RStudio is boosting productivity and making the process in which is embedded more efficient (cost reduction).
Time to market ROI is massive vs hiring the full-time dedicated team to build and maintain a frontend multi-tenant SaaS data viz product.
It will be interesting to see over time how the advanced features play out in terms of usability and end value, such as Natural Search, which we are very excited about, and the machine learning tools.