Databricks Data Intelligence Platform vs. MLReef

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Databricks Data Intelligence Platform
Score 8.4 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
MLReef
Score 9.1 out of 10
Enterprise companies (1,001+ employees)
MLReef is a Machine Learning development platform that aims to democratize ML innovation across the entire organization. Distributed ML Development: - up to 5X in ML development throughput - up to 85% less dependency on internal data science capacity - Distributed workload on complex data tasks with seamless involvable domain experts - Higher acceptance of deploye models ad development is a joint task Q: What is Distributed ML…N/A
Pricing
Databricks Data Intelligence PlatformMLReef
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 PlatformMLReef
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Databricks Data Intelligence PlatformMLReef
Top Pros
Top Cons
Best Alternatives
Databricks Data Intelligence PlatformMLReef
Small Businesses

No answers on this topic

IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Snowflake
Snowflake
Score 9.0 out of 10
Posit
Posit
Score 9.1 out of 10
Enterprises
Snowflake
Snowflake
Score 9.0 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Databricks Data Intelligence PlatformMLReef
Likelihood to Recommend
8.4
(17 ratings)
9.1
(1 ratings)
Usability
9.5
(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 Data Intelligence PlatformMLReef
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.
Read full review
MLReef
Works well if you have to involve different roles in different organizations in a project. Less suited when you have a complex system of custom developed tools
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
Read full review
MLReef
  • Helps us to take on more client projects
  • Can be used by data analysts as well as casual users
Read full review
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
Read full review
MLReef
  • Out of the box support for major cloud vendors
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
Read full review
MLReef
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.
Read full review
MLReef
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.
Read full review
MLReef
No answers on this topic
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.
Read full review
MLReef
  • We can handle 4 to 6 times more projects at the same time with our team
  • We stay engaged with our customers well beyond the project duration
Read full review
ScreenShots

MLReef Screenshots

Screenshot of ML Pipeline creation - from fully flexible git repositories to addressable, explorable and easy accessible drag-and-drop elementsScreenshot of A knowledgebase for your organization: ML Projects and AI Modules (scripts)Screenshot of Full version control and transparent experiment trackingScreenshot of Repositories to manage your scripts (SCM) and data (pipelines)Screenshot of Manage your team, groups and projects with access rights and granular permissions