Dremio vs IBM Watson Explorer comparison

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Executive Summary

We performed a comparison between Dremio and IBM Watson Explorer based on real PeerSpot user reviews.

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To learn more, read our detailed Data Science Platforms Report (Updated: March 2024).
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Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Dremio gives you the ability to create services which do not require additional resources and sterilization.""The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory.""Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it.""Everyone uses Dremio in my company; some use it only for the analytics function.""We primarily use Dremio to create a data framework and a data queue.""Dremio allows querying the files I have on my block storage or object storage."

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"The ability to easily pull together lots of different pieces of information and drill down in a smarter way than has been possible with other analytics tools is key. Watson is all based on a set of AI and deep learning, machine-learning capabilities, and it is looking behind the scenes at some relationships that you likely would not have spotted on your own. It's pulling things together, categorizing some things, that are not something that you might have seen on your own.""We take natural language that was happening in our repositories and our application and then feed it to the Watson APIs. We receive JSON payloads as an API response to get cognitive feedback from the repository data.""For me, as a user, the most valuable feature is the ability to ingest and then retrieve information from a range of separate sources; the ability to dissect questions in context and actually answer them.""Ease of use is pretty good as is the standardization of not actually having to have my own natural learning algorithms, just to use the Watson APIs.""I have found the auto-generated document very useful as well as the main keywords that are highlighted, which are used for the search functionality within IBM Watson Explorer.""The valuable feature of Watson Explorer for us is data entities, and to see the hidden insights from within unstructured data."

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Cons
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported.""It shows errors sometimes.""Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement.""They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people.""Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake.""We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."

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"Much of IBM operates this way, where they have sets of tools that are in the middleware space, and it becomes the customer's responsibility or the business partner's responsibility to develop full solutions that take advantage of that middleware. I think IBM's finding itself in that spot with Watson-related technologies as well, where the capabilities to do really interesting and useful things for customers is there, but somebody still has to build it. Is that going to be the customer? Are they going to be willing to take on that responsibility themselves""It is a little bit tricky to get used to the workflow of knowing how to train Watson, what can be provided, what can't be, how to provide it, how to import, export, and what it means every time you have to add a new dictionary""The solution is expensive.""It needs better language support, to include some other languages. Also, they should improve the user interface.""More cognitive feedback would be good. The natural language analysis is great, the sentiment analyzers are great. But I would just like to see more... innovation done with the Watson platform.""Stability is actually one of the areas that could use improvement. Setting it up is always tough. Setting Explorer requires experts, but also the underlying platform is not that stable. So it really needs a good expert to keep it running.""Small businesses will probably have a little harder time getting into it, just because of the amount of resources that they have available, both financial and time, but it really is a solution that should work for them.""I would say, give some kind of a community edition, a free edition. A lot of companies do, even Amazon gives you some kind of trial and error opportunities. If they could provide something like that, it would be good."

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Pricing and Cost Advice
  • "Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
  • "Dremio is less costly competitively to Snowflake or any other tool."
  • More Dremio Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Dremio allows querying the files I have on my block storage or object storage.
    Top Answer:Every tool has a value based on its visualization, and the pricing is worth its value.
    Top Answer:Dremio's interface is good, but it has a few limitations. I cannot do a lot of things with ANSI SQL or basic SQL. I cannot use the recursive common table expression (CTE) in Dremio because the support… more »
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    Ranking
    8th
    Views
    2,693
    Comparisons
    2,048
    Reviews
    6
    Average Words per Review
    530
    Rating
    8.7
    8th
    out of 18 in Data Mining
    Views
    117
    Comparisons
    88
    Reviews
    0
    Average Words per Review
    0
    Rating
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    Comparisons
    Also Known As
    IBM WEX
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    Dremio
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    Overview

    Dremio is a data lake query engine tool that creates PDSs and VDSs on top of S3 buckets. It is used for managing simple ad-hoc queries and as a greater layer for ad-hoc queries. The most valuable features of Dremio include its ability to sit on top of any data storage, generate refresh reflections and create visuals, manage changes effectively through data lineage and data providence capabilities, use open-source, and address the problem of data transfer when working with large datasets. The use cases are broad, allowing for high-performance queries from a data lake.

    IBM Watson Explorer is a cognitive exploration and content analysis platform that lets you listen to your data for advice. Explore and analyze structured, unstructured, internal, external and public content to uncover trends and patterns that improve decision-making, customer service and ROI. Leverage built-in cognitive capabilities powered by machine learning models, natural language processing and next-generation APIs to unlock hidden value in all your data. Gain a secure 360-degree view of customers, in context, to deliver better experiences for your clients.

    Sample Customers
    UBS, TransUnion, Quantium, Daimler, OVH
    RIMAC, Westpac New Zealand, Toyota Financial Services, Swiss Re, Akershus University Hospital, Korean Air Lines, Mizuho Bank, Honda
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm31%
    Computer Software Company11%
    Manufacturing Company8%
    Retailer5%
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm10%
    Educational Organization9%
    Government9%
    Company Size
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise11%
    Large Enterprise74%
    REVIEWERS
    Small Business18%
    Midsize Enterprise18%
    Large Enterprise64%
    VISITORS READING REVIEWS
    Small Business25%
    Midsize Enterprise11%
    Large Enterprise64%
    Buyer's Guide
    Data Science Platforms
    March 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    Dremio is ranked 8th in Data Science Platforms with 6 reviews while IBM Watson Explorer is ranked 8th in Data Mining. Dremio is rated 8.6, while IBM Watson Explorer is rated 8.4. The top reviewer of Dremio writes "Quick database capabilities but sometimes shows minor errors". On the other hand, the top reviewer of IBM Watson Explorer writes "Ingests, retrieves information from a range of sources; enables dissecting questions in context and answering them". Dremio is most compared with Databricks, Snowflake, Starburst Enterprise, Amazon Redshift and Microsoft Azure Synapse Analytics, whereas IBM Watson Explorer is most compared with Salesforce Einstein Analytics, Microsoft Power BI, Tableau and KNIME.

    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.