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Databricks vs IBM Planning Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
6.6
Organizations experience mixed returns from Databricks, with benefits from cost savings and efficiency, but challenges in initial migration.
Sentiment score
6.8
IBM Planning Analytics boosts budgeting productivity but faces challenges from rising costs, prompting some companies to explore alternatives.
When it comes to big data processing, I prefer Databricks over other solutions.
For a lot of different tasks, including machine learning, it is a nice solution.
 

Customer Service

Sentiment score
7.2
Databricks customer service is generally effective with prompt responses, though some report issues mainly with third-party support channels.
Sentiment score
6.0
IBM Planning Analytics support is positive, yet response times vary; documentation, training, and multi-level support are valued.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
Instead, we rely on third-party partners recognized by IBM, who provide cost-effective support.
We have a multi-level support system, with the initial level handled by the company we bought the license from and subsequent support from IBM.
 

Scalability Issues

Sentiment score
7.4
Databricks is praised for efficient scalability and cloud compatibility, allowing easy resource adjustment across diverse projects and industries.
Sentiment score
7.5
IBM Planning Analytics excels in scalability and real-time data, though complexity and pricing pose challenges for some users.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is an easily scalable platform.
Scalability is quite hard to implement in TM1, largely since the on-premise installation chosen back in 2014.
Scalability is straightforward but it is pricey since it's a SaaS model priced per user.
 

Stability Issues

Sentiment score
7.6
Databricks is stable and efficient for large data, with minor issues during updates and occasional connectivity challenges.
Sentiment score
7.7
IBM Planning Analytics is stable and reliable, praised for robustness, supporting budgeting in various industries with few issues.
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
They release patches that sometimes break our code.
Cluster failure is one of the biggest weaknesses I notice in our Databricks.
A stable platform prevents loss of time during this process.
 

Room For Improvement

Databricks users desire improved UI, enhanced data visualization, better integration, clearer error messages, robust support, and comprehensive documentation.
IBM Planning Analytics needs improved integration, pricing, visualization, user interface, functionality, automation, design, speed, and predictive analytics support.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
This feature, if made publicly available, may act as a game-changer, considering many global organizations use SAP data for their ERP requirements.
We could use their job clusters, however, that increases costs, which is challenging for us as a startup.
The abundance of features results in complexity, requiring strict guidelines for developers to ensure simplistic approaches are adhered to.
IBM's visualization needs significant improvement.
 

Setup Cost

Databricks pricing depends on usage, with flexibility in licensing, and can vary in competitiveness compared to other solutions.
Enterprise IBM Planning Analytics has setup costs from consulting fees and varied licensing, offering market-standard ROI and compatibility.
It is not a cheap solution.
Given the product's old architecture and interface, they need to make it more affordable.
While IBM's solutions were costly before, the introduction of SaaS models has reduced prices significantly.
 

Valuable Features

Databricks provides a unified platform for data engineering, machine learning, seamless cloud integration, and robust data management capabilities.
IBM Planning Analytics enhances planning with flexible design, Excel integration, sandbox testing, machine learning, and user-friendly interface.
Databricks' capability to process data in parallel enhances data processing speed.
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
Developers can share their notebooks. Git and Azure DevOps integration on the Databricks side is also very helpful.
It also integrates machine learning and AI engines, enabling us to use algorithms for inventory forecasting which optimizes our inventory and replenishment rates.
Its stability helps controllers win time in their planning processes.
 

Categories and Ranking

Databricks
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
89
Ranking in other categories
Cloud Data Warehouse (7th), Data Science Platforms (1st), Streaming Analytics (1st)
IBM Planning Analytics
Average Rating
8.4
Reviews Sentiment
6.8
Number of Reviews
25
Ranking in other categories
Business Performance Management (3rd)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 8.8%, up 3.7% compared to last year.
IBM Planning Analytics, on the other hand, focuses on Business Performance Management, holds 8.6% mindshare, down 9.4% since last year.
Cloud Data Warehouse
Business Performance Management
 

Featured Reviews

ShubhamSharma7 - PeerSpot reviewer
Capability to integrate diverse coding languages in a single notebook greatly enhances workflow
Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.
Gnanavel-Chakkarapani - PeerSpot reviewer
Can easily create dashboards and helps businesses improve forecasting accuracy
The product has improved our company's forecasting accuracy since it serves as a very useful tool for our sales and controller teams as they easily get to enter the inputs using views in TM1, which gets loaded into our main database. If there are sales team members in different parts of the world, like in Hong Kong and Singapore, they may prefer to use IBM Planning Analytics, which is easy to use when compared to the Excel tool. Speaking about planning analytics and data analysis, I would say that our company used to use IBM Cognos Analytics for reporting, where we used to use Cognos Dynamic Cubes so that users can easily use its drag and drop features while getting to see the data for which the users had to wait for two to three minutes prior to its use. In our company, tons of data are loaded into the memory, and users can use Cognos Dynamic Cubes to analyze data and understand it. The AI capabilities of IBM have benefited our planning strategy as they are very useful for business. The tool allows the easy creation of dashboard reports using AI capabilities. No technical knowledge is required for business use cases. It is possible to integrate the product in scenarios where some new integrations are available. I remember that my company used Azure Data Factory to connect Azure, Oracle, and IBM WebSphere Application Server. When it comes to IBM Planning Analytics, it is complex to integrate it with LDAP and or any other authentication tool offered by Microsoft. In our company, some users like to integrate IBM Planning Analytics with the common LDAP or Microsoft AD, which we currently use for all our applications. The authentication part is difficult to configure with IBM Planning Analytics. The maintenance of the product is easy. My company has scheduled maintenance on the product every week, especially during forecast times, so that memories automatically lapse and users can freely access their servers. The use of the tool has had an impact on collaboration within our company's planning team since everyone knows how to easily access the data and publish the results. I recommend the product to those who plan to use it. I rate the tool a nine out of ten.
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
Educational Organization
41%
Financial Services Firm
10%
Manufacturing Company
7%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
What do you like most about IBM Planning Analytics?
The most valuable features of IBM Planning Analytics for streamlining planning processes include a unified database where all data are centralized.
What is your experience regarding pricing and costs for IBM Planning Analytics?
TM1 is quite expensive, and I'd rate the pricing as an eight out of ten. While we do get what we want in terms of functionalities and compatibility with other IBM tools, given the product's old arc...
What needs improvement with IBM Planning Analytics?
Since I'm using TM1 as an old version of Planning Analytics, it wouldn't be fair to specify what needs improvement because it's possible these issues have already been addressed in newer versions. ...
 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
Cognos TM1, IBM Cognos TM1
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
ManpowerGroup, Convergys, AIG, Orchard Brands, Citibank, InterGen, Northwestern University, EF Education First, Ironside, Bazan Group, CSOB Insurance, Macquarie Group, Charles Stanley, SATO, Government of Sint Maarten, BMW Financial Services
Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse. Updated: April 2025.
849,686 professionals have used our research since 2012.