Databricks Unified Analytics Platform Reviews

24 Ratings
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Score 8.6 out of 100

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Reviews (1-5 of 5)

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Anonymous | TrustRadius Reviewer
January 31, 2019

Databricks for modern day ETL

Score 9 out of 10
Vetted Review
Verified User
Review Source

Use Cases and Deployment Scope

Data from APIs is streamed into our One Lake environment. This one lake is S3 on AWS.
Once this raw data is on S3, we use Databricks to write Spark SQL queries and pySpark to process this data into relational tables and views.

Then those views are used by our data scientists and modelers to generate business value and use in lot of places like creating new models, creating new audit files, exports etc.
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Ann Le | TrustRadius Reviewer
March 28, 2018

If you want to be an effective ML learner, use Databricks

Score 7 out of 10
Vetted Review
Verified User
Review Source

Use Cases and Deployment Scope

I actually use Databricks for experiments and research for my master's program. I mostly use it to implement Python codes and testing the viability of the programs that I write. Many individuals in the Computer Information System department are using this software platform to implement programs. It is a good tool for us to learn [and] includes a community forum that is rather helpful if you are self-learning and have questions.
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Anonymous | TrustRadius Reviewer
August 22, 2018

Databricks Review

Score 9 out of 10
Vetted Review
Verified User
Review Source

Use Cases and Deployment Scope

We leverage Databricks (DB) to run Big Data workloads. Primarily we build a Jar and attach to DB. We do not leverage the notebooks except for prototyping.
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Anonymous | TrustRadius Reviewer
September 15, 2017

Databricks Review

Score 6 out of 10
Vetted Review
Verified User
Review Source

Use Cases and Deployment Scope

Across whole organization.

[It's] Used by self-service analysts to quickly do analysis
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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

About 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 Technical Details

Operating Systems: Unspecified
Mobile Application:No