TrustRadius: an HG Insights company

Save this comparison

Save this comparison

Add Product

Recommended Comparisons

    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Databricks Data Intelligence Platform

    Score9 out of 10
    N/ADatabricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.

    $0.07

    Per DBU

    IBM DataStage

    Score8 out of 10
    N/AIBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.N/A
    Pricing
    Databricks Data Intelligence PlatformIBM DataStage
    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 DataStage
    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 DataStage
    Considered Both Products
    Databricks
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    16 Answers
    89%
    Would buy again
    8 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    16 Answers
    100%
    Delivers good value for the price
    5 Answers
    Happy with the feature set
    94%
    Happy with the feature set
    15 Answers
    89%
    Happy with the feature set
    8 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    10 Answers
    100%
    Lived up to sales and marketing promises
    7 Answers
    Implementation went as expected
    92%
    Implementation went as expected
    12 Answers
    88%
    Implementation went as expected
    7 Answers
    Features
    Databricks Data Intelligence PlatformIBM DataStage
    Data Source Connection
    Comparison of Data Source Connection features of Databricks Data Intelligence Platform and IBM DataStage
    Feature
    Databricks Data Intelligence Platform
    -
    Ratings
    IBM DataStage
    7.7
    11 Ratings
    8% below category average
    Connect to traditional data sources00 Ratings7.911 Ratings
    Connecto to Big Data and NoSQL00 Ratings7.610 Ratings
    Data Transformations
    Comparison of Data Transformations features of Databricks Data Intelligence Platform and IBM DataStage
    Feature
    Databricks Data Intelligence Platform
    -
    Ratings
    IBM DataStage
    7.6
    11 Ratings
    7% below category average
    Simple transformations00 Ratings8.011 Ratings
    Complex transformations00 Ratings7.311 Ratings
    Data Modeling
    Comparison of Data Modeling features of Databricks Data Intelligence Platform and IBM DataStage
    Feature
    Databricks Data Intelligence Platform
    -
    Ratings
    IBM DataStage
    7.2
    11 Ratings
    10% below category average
    Data model creation00 Ratings7.18 Ratings
    Metadata management00 Ratings5.010 Ratings
    Business rules and workflow00 Ratings7.410 Ratings
    Collaboration00 Ratings7.411 Ratings
    Testing and debugging00 Ratings6.711 Ratings
    Data Governance
    Comparison of Data Governance features of Databricks Data Intelligence Platform and IBM DataStage
    Feature
    Databricks Data Intelligence Platform
    -
    Ratings
    IBM DataStage
    5.3
    10 Ratings
    42% below category average
    Integration with data quality tools00 Ratings5.310 Ratings
    Integration with MDM tools00 Ratings5.310 Ratings
    Best Alternatives
    Databricks Data Intelligence PlatformIBM DataStage
    Small Businesses
    No answers on this topic
    Skyvia
    Score10 out of 10
    Medium-sized Companies
    SAP Business Data Cloud
    Score8.6 out of 10
    IBM InfoSphere Information Server
    Score10 out of 10
    Enterprises
    SAP Business Data Cloud
    Score8.6 out of 10
    SolarWinds Task Factory
    Score8.3 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Databricks Data Intelligence PlatformIBM DataStage
    Likelihood to Recommend
    9.4
    (21 ratings)
    5.9
    (11 ratings)
    Usability
    9.7
    (7 ratings)
    8.0
    (4 ratings)
    Performance
    -
    (0 ratings)
    9.0
    (1 ratings)
    Support Rating
    8.7
    (2 ratings)
    9.6
    (3 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 DataStage
    Likelihood to Recommend
    Databricks
    Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.
    Incentivized
    Read full review
    IBM
    DataStage is somewhat outdated for an ETL. I guess that's what makes it a bit lagged behind its competitors. It can be used for data processing, sure, but its performance seems to be lagging behind or quite slow given the server it is running from. I won’t depend on this application if it's handling a lot of mission-critical banking and business data.
    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
    Incentivized
    Read full review
    IBM
    • Connect to multiple types of data-sources including Oracle, Teradata, Snowflake, SQl Server.
    • Powerful tool to load large volumes of data.
    • Transformation stages allow us to reduce the amount of code needed to create ETL scripts.
    • Allow us to synchronize and refresh data as much as needed.
    Incentivized
    Read full review
    Cons
    Databricks
    • Sometimes, when multiple jobs depend on each other in different environments, it is not always easy to see the full workflow in one place.
    • It is sometimes difficult to determine which job or cluster contributes more to the overall cost.
    • For beginners, cluster configuration may be a little difficult. So more recommendation in the platform can help.
    Incentivized
    Read full review
    IBM
    • Technical support is a key area IBM should improve for this product. Sometimes our case is assigned to a support engineer and he has no idea of the product or services.
    • Provide custom reports for datastage jobs and performance such as job history reports, warning messages or error messages.
    • Make it fully compatible with Oracle and users can direct use of Oracle ODBC drivers instead of Data Direct driver. Same for SQL server.
    Incentivized
    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
    Incentivized
    Read full review
    IBM
    Because it is robust, and it is being continuously improved. DS is one of the most used and recognized tools in the market. Large companies have implemented it in the first instance to develop their DW, but finding the advantages it has, they could use it for other types of projects such as migrations, application feeding, etc.
    Incentivized
    Read full review
    Performance
    Databricks
    No answers on this topic
    IBM
    It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
    Incentivized
    Read full review
    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
    IBM
    IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.
    Incentivized
    Read full review
    Alternatives Considered
    Databricks
    The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.
    Incentivized
    Read full review
    IBM
    With effective capabilities and easy to manipulate the features and easy to produce accurate data analytics and the Cloud services Automation, this IBM platform is more reliable and easy to document management. The features on this platform are equipped with excellent big data management and easy to provide accurate data analytics.
    Incentivized
    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.
    Incentivized
    Read full review
    IBM
    • It’s hard to say at this point, it delivers, but not quite as I expected. It takes a lot of resources to manage and sort this out (manpower, financial).
    • Definitely, I don’t have the exact numbers, but given the data it processes, it is A LOT. So props to the developer of this application.
    • Again, based on my experience, I’d choose other ETL apps if there is one that's more user-friendly.
    Read full review
    ScreenShots