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Top Rated
40 Ratings
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Score 8.8 out of 101
12 Ratings
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Score 8.6 out of 101

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Likelihood to Recommend

Anaconda

Anaconda is great for academic and private organizations that cannot afford more expensive Python/R package managers. Also, it is more appropriate for intermediate to advanced Python users--Anaconda can be somewhat frustrating for beginners, as it takes some practice to get comfortable with the workflow. I find it particularly useful for working in teams, because if everyone uses the same package manager, it is easier to troubleshoot issues and makes for reproducible research. For wealthier organizations, a premium package management system (with tech support) would be ideal. Anaconda is also great for people working independently on code development.
Maike Holthuijzen profile photo

Databricks Unified Analytics Platform

Databricks has helped my teams write PySpark and Spark SQL jobs and test them out before formally integrating them in Spark jobs. Through Databricks we can create parquet and JSON output files. Datamodelers and scientists who are not very good with coding can get good insight into the data using the notebooks that can be developed by the engineers.
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Feature Rating Comparison

Data Exploration

Anaconda
7.5
Databricks Unified Analytics Platform
6.0
Visualization
Anaconda
7.0
Databricks Unified Analytics Platform
6.0
Interactive Data Analysis
Anaconda
8.0
Databricks Unified Analytics Platform
6.0

Data Preparation

Anaconda
7.0
Databricks Unified Analytics Platform
8.0
Interactive Data Cleaning and Enrichment
Anaconda
7.0
Databricks Unified Analytics Platform
8.0
Data Transformations
Anaconda
8.0
Databricks Unified Analytics Platform
9.0
Data Encryption
Anaconda
6.0
Databricks Unified Analytics Platform
7.0
Built-in Processors
Anaconda
7.0
Databricks Unified Analytics Platform
8.0

Platform Data Modeling

Anaconda
5.7
Databricks Unified Analytics Platform
8.3
Automated Machine Learning
Anaconda
4.0
Databricks Unified Analytics Platform
8.0
Single platform for multiple model development
Anaconda
7.0
Databricks Unified Analytics Platform
9.0
Self-Service Model Delivery
Anaconda
6.0
Databricks Unified Analytics Platform
7.0
Multiple Model Development Languages and Tools
Anaconda
Databricks Unified Analytics Platform
9.0

Model Deployment

Anaconda
4.5
Databricks Unified Analytics Platform
7.5
Flexible Model Publishing Options
Anaconda
5.0
Databricks Unified Analytics Platform
7.0
Security, Governance, and Cost Controls
Anaconda
4.0
Databricks Unified Analytics Platform
8.0

Platform Connectivity

Anaconda
Databricks Unified Analytics Platform
8.3
Connect to Multiple Data Sources
Anaconda
Databricks Unified Analytics Platform
9.0
Extend Existing Data Sources
Anaconda
Databricks Unified Analytics Platform
9.0
Automatic Data Format Detection
Anaconda
Databricks Unified Analytics Platform
7.0

Pros

  • Installing packages is very easy with Anaconda. Anaconda comes with 'anaconda navigator', a terminal-like utility from which you can easily install R packages and python libraries.
  • Launching R and python IDEs as well as Jupyter notebooks from anaconda navigator is simple, and Anaconda makes it very easy to keep these packages up-to-date.
  • I really like the fact that if you don't want to install the full version of Anaconda, you can opt to install a lightweight version (called Miniconda) that includes less python libraries and only core conda. I've installed it when I didn't want to take up as much disk space as Anaconda requires, but it works just the same.
Maike Holthuijzen profile photo
  • 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
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Cons

  • It's still a little buggy. Especially the launcher.
  • It's not always easy to set up. It's not exactly difficult: a Google search away for most things, but silly stuff like path names, installing custom fonts and colors. That kind of thing.
Ayush Choukse profile photo
  • Visualization - Great area of improvement
  • Integration with Git
  • COST
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Usability

No score
No answers yet
No answers on this topic
Databricks Unified Analytics Platform9.0
Based on 1 answer
This has been very useful in my organization for shared notebooks, integrated data pipeline automation and data sources integrations. Integration with AWS is seamless. Non tech users can easily learn how to use Databricks. You can have your company LDAP connect to it for login based access controls to some extent
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Alternatives Considered

I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!
Maike Holthuijzen profile photo
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 clusters directly from notebooks was seen as a very helpful tool for non tech users.
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Return on Investment

  • It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
  • By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
  • There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.
Mauricio Quiroga-Pascal Ortega profile photo
  • Quick adoption of cloud services by end users
  • Cost is high
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Pricing Details

Anaconda

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Databricks Unified Analytics Platform

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details