Sigma Computing headquartered in San Francisco provides a suite of data services such as code free data modeling, data search and explorating, and related BI and data visualization services.
N/A
Mathematica
Score 7.0 out of 10
N/A
Wolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.
$1,520
per year
Pricing
Sigma Computing
Wolfram Mathematica
Editions & Modules
No answers on this topic
Standard Cloud
$1,520
per year
Standard Desktop
$3,040
one-time fee
Standard Desktop & Cloud
$3,344
one-time fee
Mathematica Enterprise Edition
$8,150.00
one-time fee
Offerings
Pricing Offerings
Sigma
Mathematica
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
Contact us for pricing.
Discounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
I am not an expert in any of these, though from my brief exposure to Looker it felt like a steeper learning curve, more appropriate to companies with dedicated and skilled BI engineers, whereas Sigma (and Tableau, and Looker Studio) offer a quicker and more intuitive interface …
Sigma Computing exclusively uses Snowflake as its data source, which enhances data security by not caching or extracting data locally. Tableau, on the other hand, allows a broader range of internal databases and files like SQL Server, Postgres, etc., and supports extracted …
maintianed is very user friendly. Its various ways of embedding helped us in various aspects. The usage of control ids of the filters as parameters helped us in optimizing very longSQL queries. The live Support team every weekday is a very great intiative that helped in quick …
I'd rate Sigma to be extremely similar to Sisense except it looks not as nice. I would say that as a tool, Sigma is more user-friendly than Tableau, Power BI, Trevor, and Metabase.
I do feel that Looker is far more powerful and looks great, but I also recognize that Looker does …
Sigma computing has better pricing than the competitors. We're always looking for what is good for the price but also gives us all we need to complete our reporting. It also brings about a lot of updates that are nice to see. The embedding helps other BI tools sometimes.
Sigma has a better view of tables and it is much easier to create new data sets/aggregations. Tableau is better in some visual aspects because there is more customization available, albeit more confusing than Sigma to do. Sigma is very intuitive and did not take long to learn …
Sigma Computing had better functionality and is beginner friendly. While Tableau is a more well known product, Sigma Computing has a better user interface that is easier to comprehend for those without a non-technical background. This makes it easier to showcase dashboards to …
Sigma is the easiest to use from a workbook developer perspective, and from a non-technical end user perspective. Everything from administration, semantic layer setup, to creating dashboards is easier in Sigma than these other tools. Developing content in Sigma is enjoyable, …
Sigma has the capabilities of the other BI tools. I think it's pretty user friendly and easy to learn. Many of our stakeholders are used to using Excel so it's nice that it is a smooth onboarding process for them. We haven't looked into much of the visualization capabilities so …
I have found that Tableau can be used to create a greater variety of custom and complex visuals, though these visuals are far more difficult to create in a quick turnaround. While Sigma may be more limited in terms of what types of visuals can be create or how customized they …
With Looker, to be effective, a substantial amount of coding & modeling needs to happen in LookML. Being another language to learn, users have to context switch again from at a minimum either SQL or Python into LookML. The concept of being able to source control, code review, …
Less visually appealing. Feels like fewer pixels. Harder to make graphs and visuals. Really good integration with snowflake and intuitive usage for custom equations and filters.
sorta in the middle. One thing that differs than domo or power bi, is that those softwares bring in the data into the platform, instead of how sigma runs a query against our data warehouse each time a user interacts with the dashboard (there is some small caching, so not always)
Sigma is by far the best. It is easiest to learn and easiest to use on a day to day basis. I never have to wait for dashboards to load and it's very easy to understand the variables that are going into my visualizations. Best of all I can manipulate the data within Sigma …
flexibility, works really well with snowflake, export capability, level of support, the fact that Sigma Computing is a start up and improving so quickly. Web based software
Projektspezialist bei Steffen Jäschke EinzUnt Physik, Berechnungen
Chose Mathematica
There is no other alternative that Maple from Maplesoft all over. There are other systems for mCAx that do not offer the richness and coverage of mathematical features. For example Matlab that restricts inself to matrice calculation and only the the right set of addon library …
Well, Mathematica is free at my university. As a graduate student, you can download and install Mathematica in your device after log in through your university email. Second, it has very nice platform. You can use Mathematica for many data analysis such as plotting, integration …
Matlab is an excellent tool, but it can't handle analytic manipulations in algebra, calculus and differential equations. Matlab is superior when it comes to a less steep learning curve. In terms of using only one tool for analytic and numerical calculations, Mathematica wins. …
Mathematica is good solution in some cases but doesn't perform well in other regions. Mathematica is good in solving mathematical problems but not performs well in machine learning areas. I would suggest to use TensorFlow or Keras for machine learning. Also it performs good for …
The ability to manipulate algebraic expressions, nested lists, and data structures in Mathematica was unequalled when I first did the comparison. Since then, I've stuck with Mathematica mostly because it's "the tool I know."
We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models.
Mathematica compares favorably to this alternative in terms of …
We selected Wolfram Mathematica as it offers lot of functionality that other products like MATLAB or sageMath do not have. And it also has advantages on the feature that it does share in common with other tools like sageMath, MATLAB etc. It is more powerful than MATLAB. It …
I think IBM Watson analytics is good alternative to Wolfram Mathematica. A few advantages of Mathematica over IBM Analytics is that Mathematica comes with a lot of inbuilt things like neural networks, predictive analysis geometry. And IBM analytics does not show the step by …
Scenarios where Sigma Computing is well suited: - Data Reporting and Visualisation : It is suitable for dashboards that integrate data from multiple back-office systems - Search and Filtering Capabilities: It provides a robust platform for searching through datasets and visualisations. Scenarios where Sigma Computing is less appropriate: Handling of null values and dynamic table adjustments
We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
Viewer level license is quite limited. These users can't download data or even add filters on datasets. Something to keep in mind.
Directly querying the underlying data warehouse will lead to increased usage. Not a big deal on something like Redshift, but your Snowflake consumption will increase, potentially by a lot.
Because we are very satisfied with the product and would most likely renew because of the services it provides. It is a tool that you bring into your organization and let it change the way you analyze your data, present your data and share you date within the Respective teams
It has a clean and modern interface. However, it is not completely intuitive. I think it would be better and easier to navigate with more Windows style drop down menus and/or tabls. There is a significant learning curve, but that may be due in part to the technical nature of this type of software tool.
They are very friendly and informative. They are quick in resolving our queries and help us understand very minute things as well. They are quick in creating feature tickets based on our custom requirements, and they would also create a bug ticket if there is any discrepancy and get that checked on time.
Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
I am not an expert in any of these, though from my brief exposure to Looker it felt like a steeper learning curve, more appropriate to companies with dedicated and skilled BI engineers, whereas Sigma (and Tableau, and Looker Studio) offer a quicker and more intuitive interface for smaller companies like ours without dedicated BI resources on staff.
The ability to manipulate algebraic expressions, nested lists, and data structures in Mathematica was unequalled when I first did the comparison. Since then, I've stuck with Mathematica mostly because it's "the tool I know."
Monitoring health of cloud platform has allowed the company to anticipate issues before they affect customers – Sigma prompted us building a canary monitoring process that provides customer container health.
Customer success has used an activity report to discover customers running runaway processes that they were unaware of, creating an alert to contact the customer and prevent an embarrassing situation.
Customer success uses the activity report to prompt conversations regarding increases or declines in behavior that led to increasing contract limits or addressing churn concerns.
Mathematica is our "go to" environment for developing solutions for our clients, so I suppose you could say that it is solely responsible for our revenues. On occasion we do use other platforms but Mathematica is a core component of our offer to clients.