Databricks Data Intelligence Platform vs. IBM ILOG CPLEX Optimization Studio

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Databricks Data Intelligence Platform
Score 8.6 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
IBM ILOG CPLEX Optimization Studio
Score 9.3 out of 10
N/A
IBM® ILOG® CPLEX® Optimization Studio is a prescriptive analytics solution that enables rapid development and deployment of decision optimization models using mathematical and constraint programming.
$285
per month per user
Pricing
Databricks Data Intelligence PlatformIBM ILOG CPLEX Optimization Studio
Editions & Modules
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
No answers on this topic
Offerings
Pricing Offerings
Databricks Data Intelligence PlatformIBM ILOG CPLEX Optimization Studio
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Databricks Data Intelligence PlatformIBM ILOG CPLEX Optimization Studio
Top Pros

No answers on this topic

Top Cons
Features
Databricks Data Intelligence PlatformIBM ILOG CPLEX Optimization Studio
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Databricks Data Intelligence Platform
-
Ratings
IBM ILOG CPLEX Optimization Studio
8.0
2 Ratings
4% below category average
Connect to Multiple Data Sources00 Ratings9.02 Ratings
Extend Existing Data Sources00 Ratings7.02 Ratings
Automatic Data Format Detection00 Ratings8.02 Ratings
MDM Integration00 Ratings8.02 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Databricks Data Intelligence Platform
-
Ratings
IBM ILOG CPLEX Optimization Studio
10.0
2 Ratings
17% above category average
Visualization00 Ratings10.02 Ratings
Interactive Data Analysis00 Ratings10.02 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Databricks Data Intelligence Platform
-
Ratings
IBM ILOG CPLEX Optimization Studio
7.3
2 Ratings
11% below category average
Interactive Data Cleaning and Enrichment00 Ratings5.01 Ratings
Data Transformations00 Ratings7.01 Ratings
Data Encryption00 Ratings8.02 Ratings
Built-in Processors00 Ratings9.02 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Databricks Data Intelligence Platform
-
Ratings
IBM ILOG CPLEX Optimization Studio
8.0
2 Ratings
5% below category average
Multiple Model Development Languages and Tools00 Ratings10.02 Ratings
Automated Machine Learning00 Ratings5.01 Ratings
Single platform for multiple model development00 Ratings8.02 Ratings
Self-Service Model Delivery00 Ratings9.01 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Databricks Data Intelligence Platform
-
Ratings
IBM ILOG CPLEX Optimization Studio
10.0
2 Ratings
16% above category average
Flexible Model Publishing Options00 Ratings10.02 Ratings
Security, Governance, and Cost Controls00 Ratings10.02 Ratings
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Databricks Data Intelligence PlatformIBM ILOG CPLEX Optimization Studio
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User Ratings
Databricks Data Intelligence PlatformIBM ILOG CPLEX Optimization Studio
Likelihood to Recommend
8.4
(17 ratings)
9.0
(2 ratings)
Usability
9.5
(3 ratings)
9.0
(1 ratings)
Support Rating
8.6
(2 ratings)
7.0
(1 ratings)
Contract Terms and Pricing Model
8.0
(1 ratings)
-
(0 ratings)
Professional Services
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Databricks Data Intelligence PlatformIBM ILOG CPLEX Optimization Studio
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.
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IBM
It is well suited for solving large-sized, mixed-integer, and integer programming problems. Now, the new version supports for Multi-Objective optimization along with some new algorithms such as Benders Decomposition. It is less appropriate for quadratic programming problems where the objective function is the product of multiple variables. However, it's very easy to code any problem.
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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
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IBM
  • Linear Programming
  • Mixed-Integer Linear Programming
  • Non-Linear Convex-Optimization
  • Visualization
  • Shadow Price Analysis
  • Parameter Tuning
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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
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IBM
  • Data handling from different sources like Note Pad, etc.
  • Large size of MILP problems.
  • Various parameters to set.
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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
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IBM
It's nice to use and with good optimization.
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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.
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IBM
Honestly, to say, I never contacted CPLEX but used its forum to know/clarify any issues I faced.
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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.
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IBM
IBM CPLEX Optimization Studio covers wide range of problems in comparison to Gurobi and also offers a number of visualization tools for results analysis. It has better customization and parameter tuning options in comparison to Gurobi. It offers various API integrations such as Python, Java and C++ which is not the case with Gurobi.
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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.
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IBM
  • Faster computation leading to better internal customer relations
  • Able to solve high variable problems with ease
  • Anomaly detection became easier within business
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ScreenShots