Databricks Data Intelligence Platform vs. Dremio

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Databricks Data Intelligence Platform
Score 8.5 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
Dremio
Score 8.0 out of 10
N/A
Dremio is presented as an intelligent lakehouse platform designed to eliminate bottlenecks by unifying data sources without ETL, simplifying the creation of datasets and delivering autonomous performance optimization to accelerate AI.N/A
Pricing
Databricks Data Intelligence PlatformDremio
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 PlatformDremio
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Databricks Data Intelligence PlatformDremio
Considered Both Products
Databricks Data Intelligence Platform
Chose Databricks Data Intelligence Platform
Databricks is a true all-in-one platform, and at the time of implementation, it had more features available to us, making it a clear choice over Snowflake. Moving our workloads from local computing to the servers in Databricks gave our start-up staff a great quality of life …
Chose Databricks Data Intelligence Platform
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 …
Chose Databricks Data Intelligence Platform
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 …
Chose Databricks Data Intelligence Platform
Databricks has a much better edge than Synapse in hundred different ways. Databricks has Photon engine, faster available release in cloud and databricks does not run on Open source spark version so better optimization, better performance and better agility and all kind of …
Chose Databricks Data Intelligence Platform
Databricks [Lakehouse Platform (Unified Analytics Platform)] can work with all data types in their original format while Snowflake requires additional structures to fit the data before loading it. Databricks is open source so potential is far greater.
Chose Databricks Data Intelligence Platform
Databricks provides support for CURD operations by introducing Delta Lake file format.
Cloudera doesn't have support for the same.
Chose Databricks Data Intelligence Platform
Databricks was picked among other competitors. Closest competition in our organization was H2O.ai and Databricks came out to be more useful for ROI and time to market in our internal research.
We could have used AWS products, however Databricks notebooks and ability to launch …
Chose Databricks Data Intelligence Platform
When we started using it, only the notebook experience was mature. However, DB was very helpful giving us direct support to get onto their platform. Really there was little in the way to compare to them at the time. AWS has services but not the same low-cost angle.
Chose Databricks Data Intelligence Platform
I also use Microsoft Azure Machine Learning in parallel with Databricks. They use different file formats which teach me to be flexible and able to write different programs. They are equally useful to me and I would like to master both platforms for any future usage. I do prefer …
Chose Databricks Data Intelligence Platform
Easier to set up and get started. Less of a learning curve.
Dremio

No answer on this topic

Best Alternatives
Databricks Data Intelligence PlatformDremio
Small Businesses

No answers on this topic

No answers on this topic

Medium-sized Companies
Snowflake
Snowflake
Score 8.9 out of 10
Snowflake
Snowflake
Score 8.9 out of 10
Enterprises
Snowflake
Snowflake
Score 8.9 out of 10
Snowflake
Snowflake
Score 8.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Databricks Data Intelligence PlatformDremio
Likelihood to Recommend
10.0
(0 ratings)
-
(0 ratings)
Usability
10.0
(0 ratings)
-
(0 ratings)
Support Rating
8.7
(0 ratings)
-
(0 ratings)
User Testimonials
Databricks Data Intelligence PlatformDremio
Likelihood to Recommend
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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Pros
  • There is databricks community, which is a free version. It is available for beginners to have an easy start with a big data platform. It does not have every feature of the full version but is still adequate for extremely new coders.
  • There are many resourceful training elements that are available to developers, data scientists, data engineers and other IT professionals to learn Apache Spark.
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Cons
  • 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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Usability
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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Support Rating
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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Alternatives Considered
Databricks is a true all-in-one platform, and at the time of implementation, it had more features available to us, making it a clear choice over Snowflake. Moving our workloads from local computing to the servers in Databricks gave our start-up staff a great quality of life boost.
Read full review
No answers on this topic
Return on Investment
  • ROI for us has been tremendous. Time to market by processing raw data in our big data infrastructure has been pretty fast.
  • Non engineers can easily use Databricks, hence helping business customers.
  • Thousands of different data combinations can easily be joined and used by our data teams.
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ScreenShots