TrustRadius: an HG Insights company

Save this comparison

Save this comparison

Add Product

Recommended Comparisons

    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Azure Databricks

    Score8.7 out of 10
    N/AAzure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…N/A

    IBM Cloud Pak for Data

    Score8.6 out of 10
    N/AIBM Cloud Pak for Data (formerly IBM Cloud Private for Data) provides data management, data governance, and automated data discovery and classification.N/A
    Pricing
    Azure DatabricksIBM Cloud Pak for Data
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Azure DatabricksIBM Cloud Pak for Data
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details
    More Pricing Information
    Community Pulse
    Azure DatabricksIBM Cloud Pak for Data
    Considered Both Products
    Microsoft
    No answer on this topic
    IBM
    Chose IBM Cloud Pak for Data
    Generally this tool has been very helpful and innovative because increase our workflow and collaboration using integrated multi-cloud platform. It also enables us to deploy in any flexible way like on-premises or cloud which saves time and hard disk space. It also enables us to …
    Incentivized
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    9 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    9 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    9 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    6 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    7 Answers
    Features
    Azure DatabricksIBM Cloud Pak for Data
    Platform Connectivity
    Comparison of Platform Connectivity features of Azure Databricks and IBM Cloud Pak for Data
    Feature
    Azure Databricks
    8.1
    2 Ratings
    3% below category average
    IBM Cloud Pak for Data
    -
    Ratings
    Connect to Multiple Data Sources6.22 Ratings00 Ratings
    Extend Existing Data Sources9.02 Ratings00 Ratings
    Automatic Data Format Detection9.02 Ratings00 Ratings
    MDM Integration8.01 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of Azure Databricks and IBM Cloud Pak for Data
    Feature
    Azure Databricks
    6.4
    2 Ratings
    27% below category average
    IBM Cloud Pak for Data
    -
    Ratings
    Visualization5.92 Ratings00 Ratings
    Interactive Data Analysis6.92 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of Azure Databricks and IBM Cloud Pak for Data
    Feature
    Azure Databricks
    8.0
    2 Ratings
    2% below category average
    IBM Cloud Pak for Data
    -
    Ratings
    Interactive Data Cleaning and Enrichment7.02 Ratings00 Ratings
    Data Transformations9.02 Ratings00 Ratings
    Data Encryption9.02 Ratings00 Ratings
    Built-in Processors7.12 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Azure Databricks and IBM Cloud Pak for Data
    Feature
    Azure Databricks
    8.3
    2 Ratings
    1% below category average
    IBM Cloud Pak for Data
    -
    Ratings
    Multiple Model Development Languages and Tools8.12 Ratings00 Ratings
    Automated Machine Learning9.02 Ratings00 Ratings
    Single platform for multiple model development8.02 Ratings00 Ratings
    Self-Service Model Delivery8.02 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of Azure Databricks and IBM Cloud Pak for Data
    Feature
    Azure Databricks
    8.5
    2 Ratings
    0% below category average
    IBM Cloud Pak for Data
    -
    Ratings
    Flexible Model Publishing Options8.02 Ratings00 Ratings
    Security, Governance, and Cost Controls9.02 Ratings00 Ratings
    Best Alternatives
    Azure DatabricksIBM Cloud Pak for Data
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    No answers on this topic
    Medium-sized Companies
    Anaconda
    Score8.1 out of 10
    ER/Studio Data Architect
    Score9.9 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    ER/Studio Data Architect
    Score9.9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Azure DatabricksIBM Cloud Pak for Data
    Likelihood to Recommend
    9.8
    (3 ratings)
    9.9
    (13 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    9.1
    (2 ratings)
    Usability
    8.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Azure DatabricksIBM Cloud Pak for Data
    Likelihood to Recommend
    Microsoft
    Suppose you have multiple data sources and you want to bring the data into one place, transform it and make it into a data model. Azure Databricks is a perfectly suited solution for this. Leverage spark JDBC or any external cloud based tool (ADG, AWS Glue) to bring the data into a cloud storage. From there, Azure Databricks can handle everything. The data can be ingested by Azure Databricks into a 3 Layer architecture based on the delta lake tables. The first layer, raw layer, has the raw as is data from source. The enrich layer, acts as the cleaning and filtering layer to clean the data at an individual table level. The gold layer, is the final layer responsible for a data model. This acts as the serving layer for BI For BI needs, if you need simple dashboards, you can leverage Azure Databricks BI to create them with a simple click! For complex dashboards, just like any sql db, you can hook it with a simple JDBC string to any external BI tool.
    Incentivized
    Read full review
    IBM
    IBM Cloud Pak for Data with Netezza is well suited for clients who require fast, economical analytics processing. It is not designed to be used as a transactional processing environment. For example, a large customer is using it during the point of sale process. That makes little sense in that business case. However, to take analysis to market faster, it excels well in that space.
    Incentivized
    Read full review
    Pros
    Microsoft
    • SQL
    • Data management
    • Data access
    Incentivized
    Read full review
    IBM
    • Increases our impact by combining BI skills with advanced analytics and machine learning in an easy to use visual interface.
    • Visualization and reporting.
    • Rapidly provides business -ready data to all users equally.
    • Manage data spread across distributed stores and clouds.
    Incentivized
    Read full review
    Cons
    Microsoft
    • Their pipeline workflow orchestration is pretty primitive. Lacks some common features
    • Workspace UI and navigation requires steep learning curve
    • Personally, I am not fond of their autosave feature. Its dangerous for production level notebooks scripts
    Incentivized
    Read full review
    IBM
    • Cannot save changes to some secrets in the internal vault
    • Sign-in issues on environments where IAM is enabled
    • The Enforce quotas option is disabled
    Incentivized
    Read full review
    Usability
    Microsoft
    Based on my extensive use of Azure Databricks for the past 3.5 years, it has evolved into a beautiful amalgamation of all the data domains and needs. From a data analyst, to a data engineer, to a data scientist, it jas got them all! Being language agnostic and focused on easy to use UI based control, it is a dream to use for every Data related personnel across all experience levels!
    Incentivized
    Read full review
    IBM
    No answers on this topic
    Alternatives Considered
    Microsoft
    Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse platform also fares better than it counterparts of Iceberg implementation or a loosely bound Delta Lake implementation of Synapse
    Incentivized
    Read full review
    IBM
    IBM Cloud Pak for Data takes the IBM Cognos solution and provides this on an enterprise cloud platform that can be extended to support better data integration and data science capabilities.
    Incentivized
    Read full review
    Return on Investment
    Microsoft
    • Helped reduce time for collecting data
    • Reduced cost in maintaining multiple data sources
    • Access for multiple users and management of users/data in a single platform
    Incentivized
    Read full review
    IBM
    • We have the ability to access all our data much quicker through the unified search option.
    • 30% increase in productivity through the introduction of AI.
    • Improved data security and governance.
    Incentivized
    Read full review
    ScreenShots