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Databricks in San Francisco offers the Databricks Unified Analytics Platform, a data science platform and Apache Spark cluster manager.https://dudodiprj2sv7.cloudfront.net/product-logos/wT/iW/AOTJLME221KK.pngDatabricks ReviewWe 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.,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.,9,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.,Cloudera Data Science Workbench,Amazon Redshift, AWS Lambda, PentahoDatabricks provides a cost effective end to end solution for Enterprise analyticsIt's being used for: Ingestion and cleansing of dataInteractive Analysis of dataDevelopment of Analytic ServicesProduction Environment Customer Facing Analytic Services,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,9,Rapid growth of analytics within our company. Cost model aligns with usage allowing us to make a reasonable initial investment and scale the cost as we realize the value. Platform is easy to learn and Databricks provides excellent support and training. Platform does not require a large DevOPs investmentIf you want to be an effective ML learner, use DatabricksI 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.,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.,7,Machine learning is a very new concept and not many universities offer to teach it. My school and a few others have been utilizing Databricks as one of the tools to teach and learn machine learning. By doing this, my university is creating a strong future workforce for the job market.,Azure ML,Hadoop, IBM Analytics Engine, AlexaDatabricks ReviewAcross whole organization. [It's] Used by self-service analysts to quickly do analysis,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,6,Quick adoption of cloud services by end users Cost is high,iPython and Spark,Amazon Redshift, Amazon Elastic MapReduce, AWS Lambda
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Databricks Unified Analytics Platform
10 Ratings
Score 8.3 out of 101
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Databricks Unified Analytics Platform Reviews

Databricks Unified Analytics Platform
10 Ratings
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Score 8.3 out of 101
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No photo available
August 22, 2018

Databricks Unified Analytics Platform: "Databricks Review"

Score 9 out of 10
Vetted Review
Verified User
Review Source
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.
  • 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.
  • DB generally fits 95% of what you need to do
  • Primarily the ability to transform data and or do ad-hoc DS work
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August 22, 2018

Databricks Unified Analytics Platform Review: "Databricks provides a cost effective end to end solution for Enterprise analytics"

Score 9 out of 10
Vetted Review
Verified User
Review Source
It's being used for:

  • Ingestion and cleansing of data
  • Interactive Analysis of data
  • Development of Analytic Services
  • Production Environment Customer Facing Analytic Services
  • 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
Great end to end analytics solution on AWS or Azure. Databricks continues to grow based on customer feedback. Just like everyone in the industry, they are focused on Machine Learning, but they also understand a complete solution is needed.
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Ann Le profile photo
March 28, 2018

Databricks Unified Analytics Platform Review: "If you want to be an effective ML learner, use Databricks"

Score 7 out of 10
Vetted Review
Verified User
Review Source
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.
  • 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.
Right now, I am learning about Spark ML and general machine learning concepts. It is a good practice space to run different Spark ML codes. Databricks does provide valid errors and detailed descriptions of where I can fix my code. And to run a set of codes is very easy to maneuver around. If you do not know how to code, it might be less appropriate to use Databricks. But then again, they do have a large community where help can be found.
Read Ann Le's full review
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September 15, 2017

Databricks Unified Analytics Platform: "Databricks Review"

Score 6 out of 10
Vetted Review
Verified User
Review Source
Across whole organization.

[It's] Used by self-service analysts to quickly do analysis
  • 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
When you have analysts that are not cloud-savvy, this tool helps them quickly run code and not be overwhelmed by infrastructure and optimization. [It's] Less appropriate in production deployments.
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Databricks Unified Analytics Platform Scorecard Summary

About Databricks Unified Analytics Platform

Databricks in San Francisco offers the Databricks Unified Analytics Platform, a data science platform and Apache Spark cluster manager.
Categories:  Data Warehouse,  Data Science

Databricks Unified Analytics Platform Technical Details

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Mobile Application:No