Databricks Unified Analytics Platform Reviews

24 Ratings
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Score 8.5 out of 100

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Reviews (1-5 of 5)

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March 28, 2018
Ann Le | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source

Pros and Cons

  • 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.
  • The navigation through which one would create a workspace is a bit confusing at first. It takes a couple minutes to figure out how to create a folder and upload files since it is not the same as traditional file systems such as box.com
  • Also, when you create a table, if you forgot to copy the link where the table is stored, it is hard to relocate it. Most of the time I would have to delete the table and re-created.
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January 31, 2019
Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source

Pros and Cons

  • 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
  • Databricks should come with a fine grained access control mechanism. If I have tables or views created then access mechanism should be able to restrict access to certain tables or columns based on the logged in user
  • There should be improved graphing and dash boarding provided from within Databricks
  • Better integration with AWS could help me code jobs in Databricks and run them in AWS EMR more easily using better devops pipelines
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August 22, 2018
Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
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Pros and Cons

  • Extremely Flexible in Data Scenarios
  • Fantastic Performance
  • DB is always updating the system so we can have latest features.
  • Better Localized Testing
  • When they were primarily OSS Spark; it was easier to test/manage releases versus the newer DB Runtime. Wish there was more configuration in Runtime less pick a version.
  • Graphing Support went non-existent; when it was one of their compelling general engine.
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August 22, 2018
Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source

Pros and Cons

  • Collaborative Development Environment using Notebooks.
  • Stable and Secure Cloud Development Environment requiring minimum DevOPs support
  • Fast with excellent scalability reduces time to market
  • Open source library support
  • Automation of Machine Learning Development
  • Optimization of GPU usage
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September 15, 2017
Anonymous | TrustRadius Reviewer
Score 6 out of 10
Vetted Review
Verified User
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Pros and Cons

  • Very simplified infrastructure initialization
  • Seamless and automated optimization of job execution
  • Simple tool to get used to
  • Visualization - Great area of improvement
  • Integration with Git
  • COST
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Databricks Unified Analytics Platform Scorecard Summary

Feature Scorecard Summary

Connect to Multiple Data Sources (1)
9
Extend Existing Data Sources (1)
9
Automatic Data Format Detection (1)
7
Visualization (1)
6
Interactive Data Analysis (1)
6
Interactive Data Cleaning and Enrichment (1)
8
Data Transformations (1)
9
Data Encryption (1)
7
Built-in Processors (1)
8
Multiple Model Development Languages and Tools (1)
9
Automated Machine Learning (1)
8
Single platform for multiple model development (1)
9
Self-Service Model Delivery (1)
7
Flexible Model Publishing Options (1)
7
Security, Governance, and Cost Controls (1)
8

What is Databricks Unified Analytics Platform?

Databricks in San Francisco offers the Databricks 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 all analytic processes in one place, and manage ML models across the full lifecycle. The Machine Learning Runtime (MLR) provides data scientists and ML practitioners with scalable clusters that include popular frameworks, built-in AutoML and optimizations.

Databricks Unified Analytics Platform Pricing

  • Does not have featureFree Trial Available?No
  • Does not have featureFree or Freemium Version Available?No
  • Does not have featurePremium Consulting/Integration Services Available?No
  • Entry-level set up fee?No
EditionPricing DetailsTerms
Standard$0.07Per DBU
Premium$0.10Per DBU
Enterprise$0.13Per DBU

Databricks Unified Analytics Platform Technical Details

Deployment Types:SaaS
Operating Systems: Unspecified
Mobile Application:No