Databricks Lakehouse Platform vs. Wolfram Mathematica

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Databricks Lakehouse Platform
Score 8.1 out of 10
N/A
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…
$0.07
Per DBU
Mathematica
Score 8.3 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
Databricks Lakehouse PlatformWolfram Mathematica
Editions & Modules
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
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
Databricks Lakehouse PlatformMathematica
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsDiscounts 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.
More Pricing Information
Community Pulse
Databricks Lakehouse PlatformWolfram Mathematica
Top Pros
Top Cons
Features
Databricks Lakehouse PlatformWolfram Mathematica
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
Wolfram Mathematica
9.9
6 Ratings
16% above category average
Pixel Perfect reports00 Ratings9.84 Ratings
Customizable dashboards00 Ratings9.94 Ratings
Report Formatting Templates00 Ratings9.96 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
Wolfram Mathematica
9.9
9 Ratings
21% above category average
Drill-down analysis00 Ratings9.98 Ratings
Formatting capabilities00 Ratings9.98 Ratings
Integration with R or other statistical packages00 Ratings9.97 Ratings
Report sharing and collaboration00 Ratings9.99 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
Wolfram Mathematica
9.3
8 Ratings
11% above category average
Publish to Web00 Ratings9.97 Ratings
Publish to PDF00 Ratings9.08 Ratings
Report Versioning00 Ratings9.97 Ratings
Report Delivery Scheduling00 Ratings8.95 Ratings
Delivery to Remote Servers00 Ratings8.95 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Databricks Lakehouse Platform
-
Ratings
Wolfram Mathematica
9.9
9 Ratings
19% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.99 Ratings
Location Analytics / Geographic Visualization00 Ratings9.98 Ratings
Predictive Analytics00 Ratings9.98 Ratings
Best Alternatives
Databricks Lakehouse PlatformWolfram Mathematica
Small Businesses

No answers on this topic

IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Snowflake
Snowflake
Score 9.0 out of 10
Entrinsik Informer
Entrinsik Informer
Score 9.3 out of 10
Enterprises
Snowflake
Snowflake
Score 9.0 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Databricks Lakehouse PlatformWolfram Mathematica
Likelihood to Recommend
8.4
(17 ratings)
9.9
(9 ratings)
Usability
9.4
(3 ratings)
-
(0 ratings)
Support Rating
8.6
(2 ratings)
9.5
(2 ratings)
Contract Terms and Pricing Model
8.0
(1 ratings)
-
(0 ratings)
Professional Services
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Databricks Lakehouse PlatformWolfram Mathematica
Likelihood to Recommend
Databricks
If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
Read full review
Wolfram
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.
Read full review
Pros
Databricks
  • Process raw data in One Lake (S3) env to relational tables and views
  • Share notebooks with our business analysts so that they can use the queries and generate value out of the data
  • Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
  • Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers
Read full review
Wolfram
  • It allows straightforward integration of analytic analysis of algebraic expressions and their numerical implemented.
  • Supports varying programmatic paradigms, so one can choose what best fits the problem or task: pure functions, procedural programming, list processing, and even (with a bit of setup) object-oriented programming.
  • The extensive and rich tools for graphical rendering make it very easy to not just get 2D and 3D renderings of final output, but also to do quick-and-dirty 2D and 3D rendering of intermediate results and/or debugging results.
Read full review
Cons
Databricks
  • Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
  • Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
  • Visualization in MLFLOW experiment can be enhanced
Read full review
Wolfram
  • Should include more libraries and functions.
  • Should include more functions that can be used in Machine Learning.
  • Should include more functions that can be used in Data Science.
Read full review
Usability
Databricks
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX
Read full review
Wolfram
No answers on this topic
Support Rating
Databricks
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
Read full review
Wolfram
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.
Read full review
Alternatives Considered
Databricks
Compared to Synapse & Snowflake, Databricks provides a much better development experience, and deeper configuration capabilities. It works out-of-the-box but still allows you intricate customisation of the environment. I find Databricks very flexible and resilient at the same time while Synapse and Snowflake feel more limited in terms of configuration and connectivity to external tools.
Read full review
Wolfram
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 speed of development. Mathematica compares unfavorably to this alternative in terms of license costs.
Read full review
Return on Investment
Databricks
  • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
  • DB has the ability to terminate/time out instances which helps manage cost.
  • The ability to quickly access typical hard to build data scenarios easily is a strength.
Read full review
Wolfram
  • Easy to solve huge mathematical equations, so it saved time there
  • Doing analysis and plotting graphs is also another plus point
  • Learning is very slow, and it took lot of time to learn its scripting language
Read full review
ScreenShots