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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Anaconda

    Score8.8 out of 10
    N/AAnaconda is an enterprise Python platform that provides access to open-source Python and R packages used in AI, data science, and machine learning. These enterprise-grade solutions are used by corporate, research, and academic institutions for competitive advantage and research.

    $0

    per month

    Azure Databricks

    Score8.5 out of 10
    N/AAzure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…N/A
    Pricing
    AnacondaAzure Databricks
    Editions & Modules
    Free Tier
    $0
    per month
    Starter Tier
    $15
    per month per user
    Business
    $50
    per month per user
    Custom
    Contact Sales
    No answers on this topic
    Offerings
    Pricing Offerings
    AnacondaAzure Databricks
    Free Trial
    NoNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    YesNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    AnacondaAzure Databricks
    Considered Both Products
    Anaconda
    No answer on this topic
    Microsoft
    No answer on this topic
    Key User Insights
    Would buy again
    96%
    Would buy again
    24 Answers
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    23 Answers
    No answers on this topic
    Happy with the feature set
    100%
    Happy with the feature set
    25 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    94%
    Lived up to sales and marketing promises
    15 Answers
    No answers on this topic
    Implementation went as expected
    100%
    Implementation went as expected
    21 Answers
    No answers on this topic
    Features
    AnacondaAzure Databricks
    Platform Connectivity
    Comparison of Platform Connectivity features of Anaconda and Azure Databricks
    Feature
    Anaconda
    9.3
    25 Ratings
    10% above category average
    Azure Databricks
    7.2
    4 Ratings
    16% below category average
    Connect to Multiple Data Sources9.822 Ratings6.04 Ratings
    Extend Existing Data Sources8.024 Ratings7.64 Ratings
    Automatic Data Format Detection9.721 Ratings7.14 Ratings
    MDM Integration9.614 Ratings8.03 Ratings
    Data Exploration
    Comparison of Data Exploration features of Anaconda and Azure Databricks
    Feature
    Anaconda
    8.5
    25 Ratings
    2% above category average
    Azure Databricks
    6.9
    4 Ratings
    19% below category average
    Visualization9.025 Ratings6.04 Ratings
    Interactive Data Analysis8.024 Ratings7.93 Ratings
    Data Preparation
    Comparison of Data Preparation features of Anaconda and Azure Databricks
    Feature
    Anaconda
    9.0
    26 Ratings
    9% above category average
    Azure Databricks
    8.7
    4 Ratings
    5% above category average
    Interactive Data Cleaning and Enrichment8.823 Ratings8.44 Ratings
    Data Transformations8.026 Ratings9.04 Ratings
    Data Encryption9.719 Ratings9.54 Ratings
    Built-in Processors9.620 Ratings8.04 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Anaconda and Azure Databricks
    Feature
    Anaconda
    9.2
    24 Ratings
    8% above category average
    Azure Databricks
    7.9
    4 Ratings
    7% below category average
    Multiple Model Development Languages and Tools9.023 Ratings6.14 Ratings
    Automated Machine Learning8.921 Ratings8.54 Ratings
    Single platform for multiple model development10.024 Ratings8.54 Ratings
    Self-Service Model Delivery9.019 Ratings8.54 Ratings
    Model Deployment
    Comparison of Model Deployment features of Anaconda and Azure Databricks
    Feature
    Anaconda
    9.5
    21 Ratings
    10% above category average
    Azure Databricks
    8.3
    4 Ratings
    4% below category average
    Flexible Model Publishing Options10.021 Ratings8.04 Ratings
    Security, Governance, and Cost Controls9.020 Ratings8.54 Ratings
    Best Alternatives
    AnacondaAzure Databricks
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    RapidMiner
    Score8.9 out of 10
    Medium-sized Companies
    Jupyter Notebook
    Score8.6 out of 10
    Anaconda
    Score8.8 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    IBM Watson Studio
    Score10 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    AnacondaAzure Databricks
    Likelihood to Recommend
    10.0
    (38 ratings)
    7.6
    (5 ratings)
    Likelihood to Renew
    7.0
    (1 ratings)
    -
    (0 ratings)
    Usability
    9.0
    (3 ratings)
    7.5
    (3 ratings)
    Support Rating
    8.9
    (9 ratings)
    -
    (0 ratings)
    User Testimonials
    AnacondaAzure Databricks
    Likelihood to Recommend
    Anaconda
    I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.
    Incentivized
    Read full review
    Microsoft
    Centralised notebooks are out directly into production. This can lead to poorly engineered code. It is very good for fast queries and our data team are always able to provide what we ask for. It is a big cost to our business so it is important it runs efficiently and returns on our investment.
    Incentivized
    Read full review
    Pros
    Anaconda
    • Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
    • Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
    • Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.
    Incentivized
    Read full review
    Microsoft
    • Data Processing and Transformations based on Spark
    • Delta Lakehouse when clubbed with an external cloud storage
    • Governance using Unity Catalog to unify IAM
    • Delta Live Tables is a product, which although relatively newer, has a great potential with the visuals of a pipeline.
    Incentivized
    Read full review
    Cons
    Anaconda
    • It can have a cloud interface to store the work.
    • Compatible for large size files.
    • I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.
    Incentivized
    Read full review
    Microsoft
    • Intuitive interface
    • Ease of use
    • Providing FAQ or QRGs
    Incentivized
    Read full review
    Likelihood to Renew
    Anaconda
    It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
    Incentivized
    Read full review
    Microsoft
    No answers on this topic
    Usability
    Anaconda
    I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.
    Incentivized
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    Microsoft
    The developers are able to switch between Python and SQL in the Notebook which allows the collaboration of SQL analyst and Data scientist. The integration of Mosaic AI allows users to write complex codes in natural languages. Unity catalog has centralized the security and governance features and simplified the process of maintaining it
    Incentivized
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    Support Rating
    Anaconda
    Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.
    Incentivized
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    Microsoft
    No answers on this topic
    Alternatives Considered
    Anaconda
    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!
    Incentivized
    Read full review
    Microsoft
    I have found Azure Databricks to be much better than Snowflake for handling bigger, diverse data types. Snowflake is much simpler and better for smaller warehousing. The real time processing is much better in Azure Databricks and we have much more language options. Snowflake is more expensive but simpler to use. Both are great for different needs.
    Incentivized
    Read full review
    Return on Investment
    Anaconda
    • 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.
    Incentivized
    Read full review
    Microsoft
    • The support team is amazing, they help you at every stage of the projects, from sales to delivery.
    • On a framework level, it has had an amazing impact and has reduced the clients overall data platform costs by a staggering 65%
    • There has been a 40% Manual work requirement on average for the clients when they move to Azure Databricks Data Platform
    Incentivized
    Read full review
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