Databricks Lakehouse Platform vs. IBM Watson Analytics (discontinued)

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
IBM Watson Analytics (discontinued)
Score 9.0 out of 10
N/A
N/AN/A
Pricing
Databricks Lakehouse PlatformIBM Watson Analytics (discontinued)
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 Lakehouse PlatformIBM Watson Analytics (discontinued)
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
Databricks Lakehouse PlatformIBM Watson Analytics (discontinued)
Top Pros
Top Cons
Best Alternatives
Databricks Lakehouse PlatformIBM Watson Analytics (discontinued)
Small Businesses

No answers on this topic

Saturn Cloud
Saturn Cloud
Score 9.1 out of 10
Medium-sized Companies
Snowflake
Snowflake
Score 9.0 out of 10
Posit
Posit
Score 9.0 out of 10
Enterprises
Snowflake
Snowflake
Score 9.0 out of 10
Dataiku
Dataiku
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Databricks Lakehouse PlatformIBM Watson Analytics (discontinued)
Likelihood to Recommend
8.4
(17 ratings)
6.7
(6 ratings)
Usability
9.4
(3 ratings)
-
(0 ratings)
Support Rating
8.6
(2 ratings)
-
(0 ratings)
Contract Terms and Pricing Model
8.0
(1 ratings)
-
(0 ratings)
Professional Services
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
Databricks Lakehouse PlatformIBM Watson Analytics (discontinued)
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
Despite its shortcomings, IBM Watson Analytics does its job well. It's paired for any size organization, big or small – but realistically, if you're going to be analyzing user-data on a broad scale, it probably makes sense to use this program if you're working with a big company. Otherwise Facebook Analytics could probably do the work for you, for a cheaper price. Our social media manager has been using it to track data for a client of ours, and they have been enjoying it so far. It's a good system to determine user traffic.
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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
  • IBM Bluemix provides a wealth of powerful APIs. The ones I tried were easy to use and required minimal training to get up to speed.
  • I'd rate the documentation 9/10 as it was easy to navigate, had good examples and explained most of the possible inputs/outputs.
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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
  • Documentation is really hard to search through and follow along with. Needs a lot more examples and guidance.
  • Pricing isn't clear a lot of the time. As a developer trying new stuff, I've been hit with charges and been unsure where the usage came from. Would be good for this to be easier to follow up. Had asked support staff and got no reply.
  • The interface can be overwhleming.
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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
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.
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IBM
No answers on this topic
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
Most commonly, if you're comparing it against other brands – my favorite being Google Analytics – this essentially does the same thing. It really just depends on what platform you're most comfortable working with. Google and IBM both have great software, and ease of use (assuming you know what you're doing when you get started). Although Google doesn't go as in-depth with their data analysis as IBM
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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
  • See previous notes. We decided, for good reason, not to pursue any real production applications with the Bluemix products because we, our management, and our customer and their management realized it would not work in a real-world, down and dirty production environment where company reputations, financial performance, and customer satisfaction were at stake!
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ScreenShots