Anaconda vs. Azure Synapse Analytics

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Anaconda
Score 8.3 out of 10
N/A
Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and research. Anaconda also provides enterprise-grade security to open-source software through the Premium Repository.
$0
per month
Azure Synapse Analytics
Score 6.9 out of 10
N/A
Azure Synapse Analytics is described as the former Azure SQL Data Warehouse, evolved, and as a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives users the freedom to query data using either serverless or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.
$4,700
per month 5000 Synapse Commit Units (SCUs)
Pricing
AnacondaAzure Synapse Analytics
Editions & Modules
Free Tier
$0
per month
Starter Tier
$9
per month
Business Tier
$50
per month per user
Enterprise Tier
60.00+
per month per user
Tier 1
$4,700
per month 5,000 Synapse Commit Units (SCUs)
Tier 2
$9,200
per month 10,000 Synapse Commit Units (SCUs)
Tier 3
$21,360
per month 24,000 Synapse Commit Units (SCUs)
Tier 4
$50,400
per month 60,000 Synapse Commit Units (SCUs)
Tier 5
$117,000
per month 150,000 Synapse Commit Units (SCUs)
Tier 6
$259,200
per month 360,000 Synapse Commit Units (SCUs)
Offerings
Pricing Offerings
AnacondaAzure Synapse Analytics
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 Synapse Analytics
Top Pros
Top Cons
Features
AnacondaAzure Synapse Analytics
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Anaconda
9.3
25 Ratings
11% above category average
Azure Synapse Analytics
-
Ratings
Connect to Multiple Data Sources9.822 Ratings00 Ratings
Extend Existing Data Sources8.024 Ratings00 Ratings
Automatic Data Format Detection9.721 Ratings00 Ratings
MDM Integration9.614 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Anaconda
8.5
25 Ratings
2% above category average
Azure Synapse Analytics
-
Ratings
Visualization9.025 Ratings00 Ratings
Interactive Data Analysis8.024 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Anaconda
9.0
26 Ratings
10% above category average
Azure Synapse Analytics
-
Ratings
Interactive Data Cleaning and Enrichment8.823 Ratings00 Ratings
Data Transformations8.026 Ratings00 Ratings
Data Encryption9.719 Ratings00 Ratings
Built-in Processors9.620 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Anaconda
9.2
24 Ratings
9% above category average
Azure Synapse Analytics
-
Ratings
Multiple Model Development Languages and Tools9.023 Ratings00 Ratings
Automated Machine Learning8.921 Ratings00 Ratings
Single platform for multiple model development10.024 Ratings00 Ratings
Self-Service Model Delivery9.019 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Anaconda
9.5
21 Ratings
11% above category average
Azure Synapse Analytics
-
Ratings
Flexible Model Publishing Options10.021 Ratings00 Ratings
Security, Governance, and Cost Controls9.020 Ratings00 Ratings
Best Alternatives
AnacondaAzure Synapse Analytics
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.2 out of 10
Google BigQuery
Google BigQuery
Score 8.7 out of 10
Medium-sized Companies
Posit
Posit
Score 9.8 out of 10
Snowflake
Snowflake
Score 8.9 out of 10
Enterprises
Posit
Posit
Score 9.8 out of 10
Snowflake
Snowflake
Score 8.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
AnacondaAzure Synapse Analytics
Likelihood to Recommend
10.0
(38 ratings)
8.1
(9 ratings)
Likelihood to Renew
7.0
(1 ratings)
-
(0 ratings)
Usability
9.0
(3 ratings)
9.6
(2 ratings)
Support Rating
8.9
(9 ratings)
9.6
(2 ratings)
Contract Terms and Pricing Model
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
AnacondaAzure Synapse Analytics
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.
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Microsoft
It's well suited for large, fastly growing, and frequently changing data warehouses (e.g., in startups). It's also suited for companies that want a single, relatively easy-to-use, centralized cloud service for all their data needs. Larger, more structured organizations could still benefit from this service by using Synapse Dedicated SQL Pools, knowing that costs will be much higher than other solutions. I think this product is not suited for smaller, simpler workloads (where an Azure SQL Database and a Data Factory could be enough) or very large scenarios, where it may be better to build custom infrastructure.
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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.
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Microsoft
  • Create data pipelines to connect with multiple data workspace(s) and external data
  • Ability to connect with Azure Data Lake (sequentially) for data warehousing
  • Being able to manage connections and create integration runtimes (for onPrem data capture)
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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.
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Microsoft
  • It takes some time to setup a proper SQL Datawarehouse architecture. Without proper SSIS/automation scripts, this can be a very daunting task.
  • It takes a lot of foresight when designing a Data Warehouse. If not properly designed, it can be very troublesome to use and/or modify later on.
  • It takes a lot of effort to maintain. Businesses are continually changing. With that, a full time staff member or more will be required to maintain the SQL Data Warehouse.
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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.
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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.
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Microsoft
The data warehouse portion is very much like old style on-prem SQL server, so most SQL skills one has mastered carry over easily. Azure Data Factory has an easy drag and drop system which allows quick building of pipelines with minimal coding. The Spark portion is the only really complex portion, but if there's an in-house python expert, then the Spark portion is also quiet useable.
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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.
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Microsoft
Microsoft does its best to support Synapse. More and more articles are being added to the documentation, providing more useful information on best utilizing its features. The examples provided work well for basic knowledge, but more complex examples should be added to further assist in discovering the vast abilities that the system has.
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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!
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Microsoft
When client is already having or using Azure then it’s wise to go with Synapse rather than using Snowflake. We got a lot of help from Microsoft consultants and Microsoft partners while implementing our EDW via Synapse and support is easily available via Microsoft resources and blogs. I don’t see that with Snowflake
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Contract Terms and Pricing Model
Anaconda
No answers on this topic
Microsoft
Basically, the billing is predictable, and this all about it.
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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.
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Microsoft
  • We have had an improvement in our overall processing time
  • Cost was much lower than most of its competitors
  • Our reporting needs have grown and housing the data here has been great
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