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4-star reviews ( Show all reviews )

    reviewer2775498

Isolate environments and switch package versions efficiently for smoother testing workflows

  • November 15, 2025
  • Review from a verified AWS customer

What is our primary use case?

My main use case for Anaconda Business is testing. I usually use it to create environments, install packages, and check how smoothly everything works. I also test its security features, performance, and overall user experience to see if there are any issues or improvements needed.

Recently, I tested how Anaconda Business handles environment creation with multiple packages. I tried creating a new environment with a mix of data science libraries such as Pandas, NumPy, and Scikit-learn to see if there were any conflicts or dependency issues. I also checked how fast the environment was created and whether the package installations were smooth. Everything worked fine, but I did notice a small delay when installing larger libraries, which stood out to me during the test.

Anaconda Business helps a lot when I need to test different versions of packages. Switching between versions is really easy, so it saves time when I am trying to reproduce issues or compare behavior. It also helps keep everything stable because the environments stay consistent even after updates, which definitely made a difference.

What is most valuable?

The best features of Anaconda Business, in my view, are the environment and package management tools, the security and governance features, and the ability to switch and test different versions easily. Of these, I find the environment isolation and version management most valuable because they make testing and reproducing issues so much smoother. The security controls are also important because they give me confidence that what I am testing is safe and compliant.

I use the environment isolation and version management features almost every day. Whenever I need to test something, I just create a fresh environment, so nothing interferes with the packages I am working with. It saves a lot of time because I do not have to clean up or fix conflicts from older setups. One example is when I had to test the same script with two different versions of Pandas. Instead of uninstalling and reinstalling packages repeatedly, I just made two separate environments, one with the older version and one with the newer version. That made it really easy to compare the behavior and find where the issue was, and it honestly saved me a lot of effort and helped me finish the test much faster.

One thing I have really found helpful, but people do not talk about much, is how stable the environment stays. Even after a lot of installs and changes, they do not get messed up easily, which makes my testing a lot smoother. Another small hidden gem for me is the ability to clone environments. If I want to try something risky, I just make a quick copy and experiment there without worrying about breaking my main setup. It sounds simple, but it has honestly saved me a lot of stress and time.

The biggest positive impact has been the consistency it brings. Since everyone can use clean, isolated environments, we run into far fewer package conflicts or situations where something works on one system but not another. It has made testing smoother and has reduced the time we spend troubleshooting setup problems. Another improvement I have noticed is that it is easier to reproduce bugs now. I just create the same environment and rerun the test. Overall, it has helped make our workflow more organized and predictable.

What needs improvement?

Overall, it works well, but there are a few things that could be better. Sometimes the environment creation or package installation feels a bit slow, especially with bigger libraries. Another thing I would appreciate is a cleaner, more intuitive interface for managing environments. It works, but a smoother UI could make the workflow faster. It would also be nice to have clearer error messages when something fails, so it is easier to understand what went wrong without digging too much.

The documentation could be a bit clearer, especially for troubleshooting specific errors or setup issues. Sometimes I need to search extensively to find the exact steps. Also, having quicker or more detailed support responses would help when something unexpected comes up. These are not major problems, but improving them would definitely make the overall experience smoother.

One small improvement I would add is smoother integration with IDEs. It works fine right now, but having even tighter or more automated syncing with tools such as VS Code or PyCharm would make the workflow faster. Perhaps also a few more built-in examples or quick-start guides for common setups would be helpful. Nothing major, just things that would make the experience even more user-friendly.

For how long have I used the solution?

I have been working at TCS for four years.

What do I think about the stability of the solution?

We actually noticed a few small but clear improvements after using Anaconda Business. For example, we spend a lot less time fixing environment issues now. Earlier, setting up or troubleshooting conflicts could take anywhere from thirty minutes to an hour, but now most setups just work. That is easily a time-saver every week. We have also seen fewer repeat bugs caused by mismatched package versions. Since everyone can use the same isolated environment, the number of those version mismatch errors has definitely gone down. It is not a formal metric, but you can feel the difference in how smooth testing has become.

What do I think about the scalability of the solution?

In my experience, Anaconda Business scales pretty well. As more environments or users get added, it still runs smoothly without major slowdowns. It feels reliable, even when handling multiple environments or heavier packages. Overall, the scalability has been solid for our needs.

How are customer service and support?

We have not had to contact support very often, but the few times we did, the experience was decent. The responses were helpful, though sometimes it took a little longer than expected to get a detailed answer. Overall, support was reliable when we needed it, just not super-fast every single time.

How would you rate customer service and support?

Neutral

Which solution did I use previously and why did I switch?

Before this, we mostly used regular open-source Anaconda and sometimes managed environments manually. It worked, but we ran into version conflicts and setup issues more often. We switched to Anaconda Business because it offered better scalability, stability, security, and governance, which made our testing workflow much smoother.

How was the initial setup?

Overall, the pricing and licensing felt reasonable for what the platform offers. The setup cost was not too heavy either. Once everything was configured, it was pretty straightforward to get started. The licensing process was clear enough, though a bit more flexibility or transparency in the pricing structure would always be helpful. But in general, we did not run into any major issues.

What about the implementation team?

We did not purchase it through the AWS marketplace. It was arranged separately.

What was our ROI?

We have definitely seen a return on investment, mostly in terms of time saved. For example, we used to spend a lot of time fixing environment issues or dealing with version mismatches. Now, these problems have dropped a lot. I would say we easily save a few hours each week as a team. It is not about needing fewer people, but more about everyone being able to work smoothly without unnecessary delays. The main ROI has been time saving and fewer interruptions, which adds up over the long run.

Which other solutions did I evaluate?

We did evaluate a few options before choosing Anaconda Business. We looked at using plain Conda with manual controls, virtual environments, and even Docker for environment isolation. They all had their strengths, but none of them gave the same level of security, governance, and centralized package management. Anaconda Business just offered a more complete setup for what we needed, especially from a testing and reliability point of view.

What other advice do I have?

My advice would be to take some time to set up your environments properly and explore the management features. It really pays off later. If you are coming from manual setups, you will notice the difference pretty quickly. Also, make sure your team aligns on using the same environments because that is where Anaconda Business really shines. Overall, it is a solid choice if you want more stability and fewer package issues.

I think we covered most of the important points. The only thing I would add is that Anaconda Business is one of those tools that you appreciate more the longer you use it. The consistency and stability really make a difference over time. I gave this review a rating of eight out of ten.

Which deployment model are you using for this solution?

Hybrid Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?


    reviewer2775636

Has improved collaboration and security with centralized package control and faster environment setup

  • November 10, 2025
  • Review from a verified AWS customer

What is our primary use case?

My main use case for Anaconda Business is enterprise data science and machine learning, along with secure package and dependency management, which I primarily use for day-to-day tasks.

A specific example of how I use Anaconda Business in my work includes tasks and projects where it has significantly helped with centralized environment management, government compliance, and related requirements.

How has it helped my organization?

Anaconda Business has positively impacted my organization in several meaningful ways.

The positive impact of Anaconda Business includes improved security and trust, better collaboration and productivity, and operational efficiency.

Specific examples of improvements since using Anaconda Business include faster environment setup, where teams can instantly create and share standardized environments, eliminating dependency hell and allowing focus on analysis rather than administrative work. Additionally, utilizing pre-vetted secure packages in the centralized repository and mirroring has provided significant benefits.

What is most valuable?

Some of the best features Anaconda Business offers include a centralized package repository, role-based access control, enterprise-grade security, consistent and reproducible environments, cloud and on-premises flexibility, and performance optimization.

I rely on the centralized package repository the most, which provides a private and secure package repository for Python and R, and it has made the biggest difference in my work.

Packages in Anaconda Business are scanned for security vulnerabilities and license compliance before release, which significantly reduces risks compared to public repositories such as PyPI and Conda-forge.

What needs improvement?

Anaconda Business can be improved by simplifying the user experience, enhancing cloud-native features, improving integration with DevOps and MLOps pipelines, adding more AI-powered management tools, expanding the package ecosystem, and developing more collaboration and knowledge-sharing features.

Additionally, stronger governance automation should be implemented, along with more educational and onboarding resources, enhanced customer feedback mechanisms, and community engagement. Pricing and licensing flexibility should also be considered.

For how long have I used the solution?

I have been using Anaconda Business for a year.

What other advice do I have?

I find Anaconda Business very helpful and convenient to use, which adds something unique to my workflow. I would rate Anaconda Business a nine out of ten.

I give it a nine because I have noticed the need for more AI-powered generating tools and better integration with DevOps pipelines, and I want to see simplified user experiences.

Anaconda Business is deployed in my organization using public cloud only. The cloud provider I use for Anaconda Business is Amazon Web Services (AWS). I purchased Anaconda Business through the AWS Marketplace.

Regarding pricing, the publicly listed prices for Anaconda Business are currently fifty US dollars per month, which I find somewhat costly for on-premises and custom enterprise deployments. Pricing for custom deployments is available through contacting sales. Additionally, according to one marketplace listing, there is a price shown of seven hundred fifty dollars per user per year. My overall rating for this product is nine out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)


    Sv Shweta

Developers have reduced setup time and ensured secure, consistent environments across teams

  • November 07, 2025
  • Review from a verified AWS customer

What is our primary use case?

I have been using Anaconda Business for one year now.

My main use case for Anaconda Business includes secure open source package usage, centralized package and environment management, secure environments, enterprise scale deployment, and data science.

One example of how I use Anaconda Business in my daily work is that without Anaconda, every developer installs packages manually, such as one person installing pandas 2.2 and another installing 2.0, which can create a legal risk if someone accidentally installs a package with a GPL license. A package update can introduce security vulnerabilities. With Anaconda Business, everyone works with the same versions, zero security warnings, and code runs the same way in development and production, which leads to less debugging, more productivity, and much more.

Anaconda Business fits well into my workflow, and there is nothing else to add about my use case.

What is most valuable?

Anaconda Business offers several best features including a trusted distribution of science curated package repositories, enterprise-grade governance and security controls, environment and dependency management for all teams across the world, and the ability to get actionable insights and monitoring for additional auditability and scalability.

Anaconda Business has positively impacted my organization by centralizing the approved environment repository, so everyone now works with the same versions, which reduces debugging time and improves collaboration. New developers or data scientists no longer spend days setting up environments manually, which is a very time-consuming process. Now they can simply run one YAML file and start working immediately, saving a lot of time for all developers and the entire team. We also achieve consistent deployment from development to test to production with expected consistency in all environments.

Regarding time saved and productivity improvements since using Anaconda Business, environment setup time for new team members previously took one to two days, but after implementing Anaconda Business, it only takes one to two hours, resulting in eighty to ninety percent time saved. Additionally, debugging due to dependency conflicts previously took three to five hours per developer each week, but now we can solve all issues within one hour, meaning sixty to seventy-five percent of time is reduced. Regarding security, before it took two to three hours per month per project, but now it is fully automated and monitored, meaning one hundred percent time is saved.

Using Anaconda Business, I have seen huge time-saving due to the automation of monitoring and deployment, which has led to significant improvements.

What needs improvement?

Anaconda Business could be improved because currently, if a package is not added to the curated repository, our teams may wait hours or days for security license validation. I suggest implementing an automated fast-track approval pipeline with risk scoring or auto approval for low-risk MIT and BSD packages. Additionally, the existing UI for environment and usage visibility can feel technical and scattered, so I would suggest a more visual dashboard that shows top-used environments, vulnerability alerts, and package version drift across teams.

I reduce the score to nine out of ten because of the UI and responsiveness of Anaconda Business. If there were a better dashboard or more insightful visualizations, that would be more helpful for all developers to monitor their tasks and environments.

For how long have I used the solution?

I have been using Anaconda Business for one year now.

What do I think about the stability of the solution?

Anaconda Business is stable with no downtime or reliability issues. Everything is going smoothly.

What do I think about the scalability of the solution?

Anaconda Business scales very well because it is built around centralized environment and package management, meaning as the number of users, projects, or ML workflows grow, Anaconda Business supports them without increasing complexity. It uses role-based access and shared environment repositories, making it easy to onboard new teams without duplications. It stores packages in Amazon S3 or internal object storage, with the repository server running on EC2 or Kubernetes that can scale vertically or horizontally.

How are customer service and support?

Anaconda Business customer support is very active with a quick response time that aligns perfectly with all our requirements. I appreciate the support team greatly.

How would you rate customer service and support?

Positive

Which solution did I use previously and why did I switch?

We did not use any solution before Anaconda Business. We later heard about it and started adapting to Anaconda Business and definitely felt a significant improvement in our team and the deployment throughout the entire process.

Which other solutions did I evaluate?

We did not evaluate other options before choosing Anaconda Business. We felt it was very useful and directly chose to use it.

What other advice do I have?

My number one advice for others looking into using Anaconda Business is to start by standardizing your environment and creating a few base environments to share them across teams early to immediately reduce dependency conflicts, as the real benefit comes from consistency. Additionally, integrating SSO and IAM from the beginning and creating a core approved package list while using Anaconda Business in CI/CD or deployment pipelines is very beneficial.

Anaconda Business simplifies deployment and promotes shared environments and standard workflows while enforcing consistency, security, and compliance across the entire data science lifecycle. It enables future scalability as ML workloads and environment complexity grow, providing a foundation that makes ML scaling smoother. Overall, it is very effective and well aligned with all my requirements.

I rate Anaconda Business a nine out of ten.

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?


    Adarsh Kv

Has ensured secure package usage and reduced version conflicts across teams

  • November 01, 2025
  • Review from a verified AWS customer

What is our primary use case?

My main use case for Anaconda Business is centralized package management and security and compliance for a private repository and team collaboration with enterprise integration in my work.

For example, my company has 50 data scientists working on different machine learning projects. Normally, everyone installs packages such as NumPy, Pandas, or TensorFlow directly from the public internet, which can cause problems including different versions of the same package causing conflicts, security vulnerabilities, or unapproved licenses, and a lack of control over what is being downloaded from the internet. With Anaconda Business, the IT admin team can host a central private repository of approved packages, block or restrict unapproved or risky packages, and ensure everyone in the company installs the same secure versions of libraries.

How has it helped my organization?

Anaconda Business has positively impacted my organization by enhancing security and compliance, providing a consistent environment across teams, improving productivity, ensuring reliable package availability even offline, streamlining governance and control, and allowing better integration with enterprise systems.

Before using Anaconda Business, our data scientists faced issues such as package version conflicts and broken dependencies when setting up environments for new projects, which has now improved productivity.

What is most valuable?

Anaconda Business's best features in my experience are a secure, curated package repository, centralized package management, access control and governance, enterprise deployment options, reproducible environments, integration with enterprise tools, and commercial support and SLAs.

Out of those, I find myself relying on centralized package management the most day-to-day as an especially valuable feature.

What needs improvement?

Interaction and speed can be improved.

For how long have I used the solution?

I have been using Anaconda Business for one year.

What do I think about the stability of the solution?

Anaconda Business is stable in my experience; I do not encounter any downtime or issues.

What do I think about the scalability of the solution?

Anaconda Business's scalability has been able to grow with my organization's needs.

How are customer service and support?

I have not interacted with their support team, so I do not have an opinion on customer support.

How would you rate customer service and support?

Negative

Which solution did I use previously and why did I switch?

Anaconda Business is the first solution we have used.

What was our ROI?

I have seen a return on investment; our employees can complete tasks in less time compared to previously, which is a great help.

What's my experience with pricing, setup cost, and licensing?

My experience with pricing, setup cost, and licensing is that it is a little costly, but it is useful.

Which other solutions did I evaluate?

Before choosing Anaconda Business, I evaluated other options such as Miniconda.

What other advice do I have?

Anaconda Business is good. My advice for others looking into using Anaconda Business is that it is best to collaborate with teams, it is easy to use, and its scalability is better. I give this product a rating of 9 out of 10.

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?


    Karthik Ganiga

Has improved compliance workflows and reduced setup time with secure package management

  • October 30, 2025
  • Review from a verified AWS customer

What is our primary use case?

Anaconda Business serves as the main solution for security and compliance, scanning packages and vulnerabilities for our organization while ensuring air-gapped and on-premise environment safe access.

Anaconda Business helps with security and compliance by blocking public packages that have malwares or license risks, keeping our company data, science, and environment secure and compliant.

It mostly helps with security and compliance by providing a safe and curated package repository and checking for vulnerabilities by scanning it, so our teams can only use trusted, approved Python or R packages.

What is most valuable?

The best features Anaconda Business offers in my experience include a secured package repository, vulnerability scanning, team collaboration tools, and enterprise integration, license, and user tracking.

The repository feature of Anaconda Business ensures that only trusted, verified Python or R packages can be used, and for integration and licensing, it helps to meet compliance requirements that we need, mainly aiding in safe, controlled, and easy Python or R management for enterprise data.

Anaconda Business positively impacts our organization by protecting us from compliance and security risks while keeping the environment consistent, allowing our team to focus on insight and innovation instead of worrying about setups, security, and software issues.

Anaconda Business provides a 60 to 70% faster environment setup, zero security incidents, lower compliance costs, and better productivity.

What needs improvement?

Anaconda Business can be improved by offering faster package updates, an enhanced user interface, better cloud integration, more detailed analytics, and improved collaboration tools.

While it is already a strong security control, it could be better with faster updates, easier usage, and deeper integration.

Anaconda Business can be improved in terms of collaborative platform features or by making it faster.

For how long have I used the solution?

I have been using Anaconda Business for the past one year.

What do I think about the stability of the solution?

Anaconda Business is stable in my experience.

What do I think about the scalability of the solution?

I rate Anaconda Business's scalability a nine.

How are customer service and support?

I would rate the customer support a seven. I have not had any experiences with Anaconda Business customer support.

How would you rate customer service and support?

Positive

Which solution did I use previously and why did I switch?

I did not previously use a different solution; this is the first one and we are using it from the beginning.

How was the initial setup?

My experience with pricing, setup cost, and licensing indicates that it is a bit costly, but it is useful.

What about the implementation team?

We are developers and not a partner; we provide some of our support or development to our clients, but we do not have a business relationship with the vendor beyond being a customer.

What was our ROI?

I have seen a return on investment with time saved by 50% and less downtime, allowing the team to deliver projects faster with fewer errors.

What's my experience with pricing, setup cost, and licensing?

My experience with pricing, setup cost, and licensing indicates that it is a bit costly, but it is useful.

Which other solutions did I evaluate?

Before choosing Anaconda Business, we first thought about Docker.

What other advice do I have?

I rate Anaconda Business 8 out of 10.

I chose 8 out of 10 due to the need for a faster environment and the collaboration tools can be improved.

I advise others looking into using Anaconda Business that it is best to use it over Docker or other options since it is faster, easy to use, and easy to collaborate.

I found this interview good, better, faster, and friendly, and I do not think anything should change for the future. My overall review rating for Anaconda Business is 8 out of 10.

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?


    Shmulik Davar

Open source platform empowers seamless integration and efficient package management

  • April 09, 2025
  • Review provided by PeerSpot

What is our primary use case?

I use Anaconda for predictions, building models, and incorporating them within the product for specific use cases.

What is most valuable?

Anaconda is an open-source platform that can integrate numerous other kits and models in one place. It offers effective package management capabilities that are beneficial. By having control over the integrations, I can do them myself without limitations.

What needs improvement?

There is room for improvement, especially regarding deployment. The process could be streamlined as the number of actions needed to deploy is quite large compared to other tools.

For how long have I used the solution?

I have been using Anaconda for the past eight or nine years.

What do I think about the stability of the solution?

The stability of Anaconda is comparable to other tools used in data science. There are always performance issues within data science, but Anaconda is not different from others.

What do I think about the scalability of the solution?

Anaconda does not have scalability restrictions as it depends on the type of machine running it.

How are customer service and support?

I have no experience with Anaconda's technical support.

How would you rate customer service and support?

Neutral

Which solution did I use previously and why did I switch?

I have used other data science platforms like H2O.ai and Dataiku but prefer Anaconda due to its open-source nature, which allows better control over what I can do.

What's my experience with pricing, setup cost, and licensing?

Anaconda is an open-source tool, so I do not pay anything for it. It is compatible with every tool, regardless of whether it is open source or a paid package.

Which other solutions did I evaluate?

I have previously used Dataiku, H2O.ai, and Databricks for data science solutions.

What other advice do I have?

The biggest disadvantage is the amount of time needed for deployment to production. My overall experience with Anaconda is positive, and I would rate it an eight out of ten.


    IshtiaqueAli

Unified platform for efficient coding and machine learning

  • September 24, 2024
  • Review provided by PeerSpot

What is our primary use case?

We use Anaconda for data science model and development, specifically for coding in Python. We use it mainly for forecasting and predicting models within the environment of Anaconda Python.

How has it helped my organization?

Anaconda has been very beneficial for our organization. The integration between different utility projects and the overall efficiency for data science and machine learning tasks has been very helpful. It provides a coding environment that saves time in setting up individual tools.

What is most valuable?

Anaconda has multiple valuable features. It provides a unified platform where you can install Jupyter, Python Spider, and other related tools without needing separate installations. The ability to work on multiple programming languages like Python, R, and Ruby is also significant. One of the best aspects is the community support.

What needs improvement?

Anaconda consumes a significant amount of processing memory when working on it. This is something that needs improvement as it can impact performance.

For how long have I used the solution?

I have been using Anaconda for four years.

What do I think about the stability of the solution?

Anaconda is stable ninety percent of the time. However, there are occasional delays due to high memory consumption.

What do I think about the scalability of the solution?

There is generally no need to scale Anaconda. The tool has minimum system requirements that need to be met for optimal performance.

How are customer service and support?

Anaconda has great community support, and its technical support is also helpful.

How would you rate customer service and support?

Positive

How was the initial setup?

The initial setup of Anaconda is straightforward. One person is enough for the installation and deployment.

What was our ROI?

Anaconda is cost-saving as it is open-source and the installation is easy. There is no need for a pricing structure for the basic version.

What's my experience with pricing, setup cost, and licensing?

Anaconda does not require a pricing structure, and it is available as an open-source tool. The features of Python, Jupyter, and others are free to use.

What other advice do I have?

I'd rate the solution nine out of ten.


    Subhransu Nayak

A cloud-based solution that can be accessed from anywhere

  • April 03, 2024
  • Review provided by PeerSpot

What is our primary use case?

I use the tool for Jupyter Notebook.

What is most valuable?

The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors.

What needs improvement?

Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring.

For how long have I used the solution?

I have been using the product for five years.

What do I think about the scalability of the solution?

Four to five developers use the product.

How are customer service and support?

I haven't contacted the tool's support team for any help or questions. I primarily use it for one of its services, and I write my own code within that service, so I haven't felt the need to contact support.

How was the initial setup?

The product is straightforward and self-explanatory. Users can easily follow the next steps provided and install it without much difficulty.

What's my experience with pricing, setup cost, and licensing?

The tool is open-source.

What other advice do I have?

Some basic tutorials can be found on YouTube, which can help you understand how Anaconda services work. Watching these tutorials can make it easier for someone to use the product. Using it for the first time can be considered at a medium difficulty level, neither too easy nor too difficult. The package management system has greatly improved my development process. I can easily install and incorporate any package I need into my work. I rate the overall product an eight out of ten.


    Mutheeswari Bose

Simplifies package and environment management across operating systems

  • March 21, 2024
  • Review provided by PeerSpot

What is our primary use case?


What is most valuable?

Voice Configuration and Environmental Management Capabilities are the most valuable features.

What needs improvement?

If we want to do some big applications, then we need to install a lot of packages. It also takes up a lot of space.

For how long have I used the solution?

I have been using Anaconda for six years.

What do I think about the scalability of the solution?

It is a scalable solution.

How was the initial setup?

The initial setup is straightforward. The deployment took twenty to thirty minutes.

What other advice do I have?

Overall, I rate the solution a nine out of ten.


    reviewer2378196

Offers free version and is helpful to handle small-scale workloads

  • March 15, 2024
  • Review provided by PeerSpot

What needs improvement?

Anaconda can't handle heavy workloads. From an improvement perspective, I want Anaconda to be able to handle heavy workloads.

For some enterprise versions or wherever there is a need for cloud-based tools to deal with large amounts of data, I feel that it would be good if Anaconda has a partnership or is able to integrate with Databricks.

For how long have I used the solution?

I have experience with Anaconda for years.

What do I think about the scalability of the solution?

In my company, around 10 to 30 people were using the product.

Which solution did I use previously and why did I switch?

In my company, I use Databricks 90 percent of the time.

How was the initial setup?

I have not encountered any challenges during the deployment process of Anaconda, especially considering that I haven't worked on heavy data.

What's my experience with pricing, setup cost, and licensing?

My company uses the free version of the tool. There is also a paid version of the tool available.

Which other solutions did I evaluate?

In terms of development, Anaconda is better than Databricks because computing costs are involved while using the latter tool. If the data is not too large and if a company can work on sample scripts while ensuring that within the organization, everything gets standardized, development can be done on Anaconda, and then users can run production scripts on Databricks because it is popularly used considering the heavy data it can manage.

What other advice do I have?

I have used the product for data engineering and for ML models.

Anaconda's ability to streamline our company's workflow in data analysis has pros and cons attached to it. In terms of pros, Anaconda's advantage over Databricks revolves around the use of system resources. Everything in Databricks is on an online computing basis, where our company uses the product's resources, but our own resources aren't utilized. In our company, we have heavy machines with us, but they aren't used when we use Databricks. I think some small-scale workloads can be handled in Anaconda. In terms of the entire lifecycle, I think Databricks has a lot of advantages over Anaconda. You have features that help you revive old models or deploy your models within the same Databricks. Databricks offers an end-to-end lifecycle over Anaconda.

Working with the integrations of various libraries and tools within Anaconda, I have not faced any issues. Anaconda offers advantages to its users when the workload or data is not much. I am not sure if the paid version of the product is on a computing basis, but if it is, then there is not much of a difference between Anaconda and the other products in the market. As per my understanding, even the enterprise version can be hosted on the company servers, so there are not many costs involved.

I recommend the product to those who plan to use it. The product can be useful in multiple sectors other than the financial sector. In the financial sector, Anaconda can be useful if the workloads are very low, there are many non-priority tasks, and the data is not much used. Issues occur when teams working in collaboration want to use Anaconda and Databricks together. I can use Anaconda for non-heavy tasks. I can go with Databricks for heavy tasks. It would be good if Anaconda and Databricks could have integration capabilities. For computing, you can use Anaconda and the resources from Databricks.

I rate the tool an eight out of ten.


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