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Databricks OverviewUNIXBusinessApplication

Databricks is #1 ranked solution in top Data Science Platforms and Streaming Analytics tools. PeerSpot users give Databricks an average rating of 8 out of 10. Databricks is most commonly compared to Microsoft Azure Machine Learning Studio: Databricks vs Microsoft Azure Machine Learning Studio. Databricks is popular among the large enterprise segment, accounting for 71% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 24% of all views.
Databricks Buyer's Guide

Download the Databricks Buyer's Guide including reviews and more. Updated: June 2022

What is Databricks?

Databricks is an industry-leading data analytics platform which is a one-stop product for all data requirements. Databricks is made by the creators of Apache Spark, Delta Lake, ML Flow, and Koalas. It builds on these technologies to deliver a true lakehouse data architecture, making it a robust platform that is reliable, scalable, and fast. Databricks speeds up innovations by synthesizing storage, engineering, business operations, security, and data science.

Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform. This enables users to easily manage a colossal amount of data and to continuously train and deploy machine learning models for AI applications. The platform handles all analytic deployments, ranging from ETL to models training and deployment.

Databricks deciphers the complexities of processing data to empower data scientists, engineers, and analysts with a simple collaborative environment to run interactive and scheduled data analysis workloads. The program takes advantage of AI’s cost-effectivity, flexibility, and cloud storage.

Databricks Key Features

Some of Databricks key features include:

  • Cloud-native: Works well on any prominent cloud provider.
  • Data storage: Stores a broad range of data, including structured, unstructured, and streaming.
  • Self-governance: Built-in governance and security controls.
  • Flexibility: Flexible for small-scale jobs as well as running large-scale jobs like Big Data processing because it’s built from Spark and is specifically optimized for Cloud environments.
  • Data science tools: Production-ready data tooling, from engineering to BI, AI, and ML.
  • Familiar languages: While Databricks is Spark-based, it allows commonly used programming languages like R, SQL, Scala, and Python to be used.
  • Team sharing workspaces: Creates an environment that provides interactive workspaces for collaboration, which allow multiple members to collaborate for data model creation, machine learning, and data extraction.
  • Data source: Performs limitless Big Data analytics by connecting to Cloud providers AWS, Azure, and Google, as well as on-premises SQL servers, JSON and CSV.

Reviews from Real Users

Databricks stands out from its competitors for several reasons. Two striking features are its collaborative ability and its ability to streamline multiple programming languages.

PeerSpot users take note of the advantages of these features. A Chief Research Officer in consumer goods writes, “We work with multiple people on notebooks and it enables us to work collaboratively in an easy way without having to worry about the infrastructure. I think the solution is very intuitive, very easy to use. And that's what you pay for.”

A business intelligence coordinator in construction notes, “The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes.”

An Associate Manager who works in consultancy mentions, “The technology that allows us to write scripts within the solution is extremely beneficial. If I was, for example, able to script in SQL, R, Scala, Apache Spark, or Python, I would be able to use my knowledge to make a script in this solution. It is very user-friendly and you can also process the records and validation point of view. The ability to migrate from one environment to another is useful.”

Databricks was previously known as Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash.

Databricks Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

Databricks Video

Databricks Pricing Advice

What users are saying about Databricks pricing:
  • "Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."
  • "We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."
  • "I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
  • "The price is okay. It's competitive."
  • "We only pay for the Azure compute behind the solution."
  • Databricks Reviews

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    Lead Data Architect at a government with 1,001-5,000 employees
    Real User
    Top 10
    Good integration with majority of data sources through Databricks Notebooks using Python, Scala, SQL, R.
    Pros and Cons
    • "The initial setup is pretty easy."
    • "Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."

    What is our primary use case?

    We used Databricks in AWS on top of s3 buckets as data lake. The primary use case was providing consistent, ACID compliant data sets with full history and time series, that could be used for analytics.

    How has it helped my organization?

    Databricks (delta lake) and the underlying files storage (data lake) is in the centre of the organisation's enterprise data hub. Most of our data is structured (csv files), have some semi-structured (json files) but we are beginning to ingest unstructured (pdf files) and use Natural Language Processing (Textract) to obtain insights driven by key words.  

    What is most valuable?

    The Databricks notebooks with SQL and Python provide good intuitive development environment. The Delta Lake, the reading of underlying file storage, the delta tables mounted on top of data lake (AWS in our case) are providing full ACID compliance, good connectivity and interoperability.   The initial setup is fairly straightforward. The stability is good.

    What needs improvement?

    The product is quite ambitious. It's trying to become a centralized platform for all data ingestion, transformation, and analytics needs. It may encounter a stiff competition from best of breed solutions powered by open source software.  Overall it's a good product, however, it might get challenged over time with with individual best-of-breed products.  For example in the area of Data Science, RStudio seems to be the industry standard at the moment. RStudio IDE is richer, there are a more out of the box functionalities like a push-button publishing, etc. It's more difficult to run R within Databricks. Especially when it comes to synchronizing the R packages, it legs behind. It's not even supporting the latest version of R 1.3. I believe eventually all analytics will converge into data science. The analytics of the future will be data science, because predicting the future will be one of the most prevalent use cases. The stuff we used to do before, slicing and dicing, drilling through, trend analysis, etc. will become redundant operations after the analytics toolsets become powered by AI/ML and fully automated. Unless the organisations acquire these platforms that can cater for machine learning and artificial intelligence, including natural language processing they will have a hard time surviving. With Databricks I would like to see more integration with and accommodation of  open-source products. This could be controversial, as it could question the whole configuration and the purpose of the product. I'm pretty sure Microsoft is trying to position it in a monopoly market as they did with Windows and MS Office so that they could charge the premium. We are beginning to see the similar product strategy behind Databricks. 
    Buyer's Guide
    Databricks
    June 2022
    Learn what your peers think about Databricks. Get advice and tips from experienced pros sharing their opinions. Updated: June 2022.
    610,045 professionals have used our research since 2012.

    For how long have I used the solution?

    I've been working with Databricks for about two years. 

    What do I think about the stability of the solution?

    From what I know and from what I've heard, talking to our data operations team, it is stable and it's quite powerful. 

    What do I think about the scalability of the solution?

    Obviously running on top of Spark, ensures fast processing and elasticity for coping with big data volumes, up to 2 petabytes. You can spin up the cluster very quickly, and shut it down. It's elastic.

    How are customer service and support?

    Excellent customer service from Databricks. Very proactive, constantly attuned to customer needs, even connected us with other customers for knowledge exchange. 

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

    I am an IT Consultant and in the past have used different solutions for ETL on top of databases, particularly if we are talking about data warehousing. However, in the last 6 years I have seen large client using a mixture of open source and proprietory technologies, like Informatica stack with data lake in AWS, or Kafka Confluence with MQ Series on top of mainframes and data lake in AWS, Databricks and Azure data lake, etc.

    How was the initial setup?

    It was pretty easy to set up. At least, that is my understanding. I'm not the data engineer though. I don't actually do installs and configurations. I explore features and build them in my architecture designs.

    What about the implementation team?

    We implemented Databricks through vendor, and the vendor was pretty good. 

    What was our ROI?

    Don't really know.

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

    I can't speak on pricing of the solution. It's not an aspect of the solution I deal with directly.

    Which other solutions did I evaluate?

    The options were Talend, EMC Isilon, native AWS services, and others.

    What other advice do I have?

    In the current capacity as and Architect and the end user of Databricks I would say I do have confidence that Databricks can provide a wealth of functionalities to start with.  My advice to future adopters of Databricks would be to be careful about the overall architectural roadmap for this application, adopt a flexible, modular, microservices like architecture whose components could be replaced in the future should they deem inadequate to cater for evolving business needs. 

    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?

    Amazon Web Services (AWS)
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    Sanjay Bheemasenarao - PeerSpot reviewer
    Director - Data Engineering expert at Sankir Technologies
    Real User
    Top 10
    Is user friendly and has great performance, but documentation needs improvement
    Pros and Cons
    • "Databricks has a scalable Spark cluster creation process. The creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance."
    • "If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."

    What is our primary use case?

    I use Databricks to explore new features and provide the industry visibility and scalability of Databricks to the companies that I work with.

    I create proof of concepts for companies. As a consultant, I also create training courses on Databricks. If a company wants to leverage a service provided by Databricks and needs to train people, they use our courses.

    What is most valuable?

    Databricks has a scalable Spark cluster creation process. The creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance.

    Databricks has made great strides in terms of performance. 

    It is very user friendly. I like the ease of creating a Spark cluster, submitting a job, or creating a notebook.

    The UI has also changed for the better compared to what it was two years ago.

    What needs improvement?

    If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks.

    It's a big ask to have people jump through a lot of hoops to get approval to create a Databricks cluster just to explore it, but if they can try it on their own with a free trial without an underlying cloud account it would be more convenient.

    Documentation can be improved as well. There are so many versions of documents. For example, when I tried to create a DBU vault and secrets file, I had to go through multiple versions of documents. This could be improved so that the documentation is easy to use.

    For how long have I used the solution?

    I've been using this solution for about two years.

    What do I think about the stability of the solution?

    Stability wise, it's quite okay. In my experience, it doesn't crash.

    What do I think about the scalability of the solution?

    I have not used autoscaling because it consumes a lot of money and because my experience has been alright. In some cases, though, it is tied to the quota of the underlying infrastructure. I have not tested the scalability to its fullest extent, but with the workloads I run, it has been fine.

    How are customer service and support?

    When I wanted to create an AWS account and contacted technical support via email, I never received a response. Recently, however, I think they have improved their support a little bit, and I did get a call in response to my question. Overall, I've not faced any issues with the person I had to contact directly.

    How was the initial setup?

    The initial setup is not very easy, but it's medium in complexity.

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

    Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price.

    What other advice do I have?

    I would rate Databricks at seven on a scale from one to ten. If you compare it to Snowflake, for example, Snowflake doesn't mandate an underlying cloud account. It creates one on its own. That's a subtle convenience that Snowflake has and one that Databricks could also build.

    Snowflake's documentation is easy to use in comparison to that of Databricks. 

    Which deployment model are you using for this solution?

    Public Cloud
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    Flag as inappropriate
    Buyer's Guide
    Databricks
    June 2022
    Learn what your peers think about Databricks. Get advice and tips from experienced pros sharing their opinions. Updated: June 2022.
    610,045 professionals have used our research since 2012.
    Chief Risk Officer at Cegid Invoice and Financing
    Real User
    It's a reasonably priced all-in-one platform that enables us to build a lakehouse framework
    Pros and Cons
    • "Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
    • "I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one."

    What is our primary use case?

    We primarily use Databricks for reporting and machine learning.

    What is most valuable?

    Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform.

    What needs improvement?

    I'm not the guy that I'm working with Databricks on a daily basis. I'm on the management team. However, my team tells me there are limitations with streaming events. The connectors work with a small set of platforms. For example, we can work with Kafka, but if we want to move to an event-driven solution from AWS, we cannot do it. We cannot connect to all the streaming analytics platforms, so we are limited in choosing the best one.

    Also, this is an all-in-one platform, but it might be preferable if there were an a la carte model where we could select the best tool in each class for reporting, machine learning, etc. I'm not yet sure if this strategy is the best one. 

    For how long have I used the solution?

    We've been using Databricks since the start of the year.

    What do I think about the stability of the solution?

    Databricks is quite stable. We haven't had any issues with stability. It's always working perfectly with no downtime.

    What do I think about the scalability of the solution?

    Databricks is based on Spark, which is based on Scala. These languages aren't easy to handle, and it's challenging to find people who know them well. At the same time, a couple of other vendors that work on top of Databricks are low-code platforms. We have to work around Databrick's lack of scalability by using low-code platforms that work on top of Databricks to give us scalability.

    How are customer service and support?

    I'll give Databricks support 10 out of 10. They are always prompt even though we didn't buy a support package. They have done an excellent job.

    How would you rate customer service and support?

    Positive

    How was the initial setup?

    Setting up Databricks is a bit complex, and the initial deployment took a few days—closer to a week. Of course, not everyone is working full-time on this. There are intervals when people are doing other stuff. 

    What was our ROI?

    It's too soon to tell what kind of return we're getting because we just started using it, and we're still migrating.

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

    The cost of Databricks is in the lower range compared to other solutions. That was one of the main reasons we chose Databricks over other vendors and platforms.  

    We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations. 

    What other advice do I have?

    I give Databricks nine out of 10. The solution has met all our expectations. I'd recommend it to a friend. It's a reasonably priced all-in-one solution that gives us data lake and lakehouse capabilities. Those were the primary reasons we chose Databricks.

    Which deployment model are you using for this solution?

    Public Cloud
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    Flag as inappropriate
    Jorge Alvarado - PeerSpot reviewer
    Owner at a marketing services firm with 1-10 employees
    Real User
    The data governance has been absolutely efficient in between other kinds of solutions
    Pros and Cons
    • "Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
    • "I would like it if Databricks made it easier to set up a project."

    What is our primary use case?

    We use Databricks for video streaming and security purposes.

    What is most valuable?

    Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions.

    What needs improvement?

    I would like it if Databricks made it easier to set up a project. The use case determines which services we are going to use. You have the application engine, and you generate a potential budget for your workloads, so you can understand what you are going to do, what you are going to use, and what you will invest in.

    Because I'm deploying on the Google Cloud Platform, measuring the investment, value, and use case is extremely difficult. So I leave it and move on without the risk. It would be easier if I had one page where you can see three columns: one for the use cases of a specific architecture, a second one for the prices based on the volume of data or machine time, and the third column for the budget. That would make it easier to know if I am using the appropriate architecture for the right solution.

    I have seen something like that in Microsoft Azure, but obviously Microsoft Azure costs a lot of money. Amazon has something like that, but it's very complicated to use.

    For how long have I used the solution?

    We've been using Databricks for about five years.

    What do I think about the stability of the solution?

    Databricks is very stable and powerful.

    What do I think about the scalability of the solution?

    It was simple to make Databricks scalable. We found that we could set up an alert to tell us if we needed more resources, money, or time from our team. We're alerted when the system detects some trigger for any use of the instance. If you have another alert from your side, that would be extremely useful because it takes a lot of time to develop that kind of trigger. 

    How are customer service and support?

    Databricks technical support was lovely. We don't need it so much, but the few questions we had were answered immediately.

    How was the initial setup?

    I am not a data engineer because I just started data science at the company, but it was straightforward and clear for the architect to set up. He provided me with that idea because he realized it would take time if we had use cases. You can select and change the data or add some modules or products. You have all the technology to do so.

    What other advice do I have?

    I rate Databricks eight out of 10. I like to move my customers into Databricks, but I take care of the internal system infrastructure so they can continue to use familiar software or operating systems and databases. They have a lot of doubts because they don't know the solution. We need to train them, explain things, and show the solution's potential value. 

    Generally, companies try to keep the same flavor when they migrate. For example, if they are using many Microsoft products, they want to work with Azure. If they are open to other options, they go with GCP or AWS. However, Databricks doesn't have enough customers here in my market because it's not a visible brand. Azure, GCP, and AWS are highly visible here, so the local teams are friendly with the three brands.

    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?

    Other
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    Flag as inappropriate
    Head of Data & Analytics at a tech services company with 11-50 employees
    Real User
    Top 5
    Helpful integration with Python and notebooks, but it should be more user-friendly and less complicated to use
    Pros and Cons
    • "The integration with Python and the notebooks really helps."
    • "Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."

    What is our primary use case?

    We are a consulting house and we employ solutions based on our customers' needs. We don't generally use products internally.

    I am a certified data engineer from Microsoft and have worked on the Azure platform, which is why I have experience with Databricks. Now that Microsoft has launched Synapse, I think that there will be more use cases.

    What is most valuable?

    You can spin up an Azure Databricks clustered, and integrating with it is seamless.

    The integration with Python and the notebooks really helps.

    What needs improvement?

    There is definitely room for improvement.

    This is the type of solution where you need to have people with technical expertise to use it.  Other products are self-service and can be employed by end-users. Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists. I'm not sure whether Databricks is working towards it, or not.

    It would be nice if it were more user-friendly, where you don't have to rely on Power BI or a visualization tool. I know that there is integration in the notebook where you can do it, but still, the relationships and semantics make it more difficult. It would be better to do it right in Databricks. You could put them within the portal and I don't have to log out and bring that into Power BI and then visualize.

    What do I think about the stability of the solution?

    We have not done any major implementation yet, although I think it's stable to an extent. I can't comment on it in terms of benchmark and experiencing any issues. It works seamlessly in the places where I've used it.

    What do I think about the scalability of the solution?

    Our implementations have been small and we haven't needed to scale as of yet. 

    Databricks can help you to build a data lake, and it's something that they need to help make more popular. People are slowly understanding it because if you look, there are lots of data lakes that people are trying to create. I'm not intimate with it, but the concept seems complicated. I think they need to write up something where videos can explain it better. What I have seen on YouTube is quite complicated for an end-user to understand.

    How was the initial setup?

    The initial setup is easy. It's not difficult when you are used to Azure.

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

    I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself. 

    The cost is difficult to estimate. I've got customers who went to the cloud and then they realized that the costs were more, compared to what they used to be on-premises. Also, because our exchange rate is so weak, I would always advocate that prices being lower is better, although I don't know how feasible it is.

    What other advice do I have?

    From a purely technical perspective, I would rate Databricks and eight out of ten. However, there is a failure in terms of user adoption. After I look at other products, including Synapse, those are better. I still feel that Databricks is quite complicated for the average person.

    I would rate this solution a five out of ten.

    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    reviewer1438992 - PeerSpot reviewer
    Security Consulting, Manager
    Vendor
    Top 5Leaderboard
    A scalable solution to quickly process and analyze streams of information
    Pros and Cons
    • "Databricks helps crunch petabytes of data in a very short period of time."
    • "Costs can quickly add up if you don't plan for it."

    What is our primary use case?

    We are working with Databricks and SMLS in the financial sector for big data and analytics. There are a number of business cases for analysis related to debt there. Several clients are working with it, analyzing data collected over a period of time and planning the next steps in multiple business divisions.

    My organization is a professional consulting service. We provide services for the other organizations, which implement and use them in a production environment. We manage, implement, and upgrade those services, but we don't use them.

    What is most valuable?

    Databricks helps crunch petabytes of data in a very short period of time for data scientists or business analysts. It helps with fraud analysis, finance, projections, etc. I like it.

    This is exactly the purpose of big data and analytics. It provides the mechanism to process and analyze a stream of information. It's best for share analysis and stream analysis.

    What needs improvement?

    Costs can quickly add up if you don't plan for it. 

    For how long have I used the solution?

    I've been using Databricks for just over a year.

    What do I think about the stability of the solution?

    Databricks is stable. It also helps that their support is included as part of the service.

    What do I think about the scalability of the solution?

    Databricks is scalable. The only issue is how much money you have for it. For example, if you need to run 100 servers, there's an eight-course with 256 gigabytes of RAM. You run out of money easily. It's charged to your credit card or your account, and you'll have to pay for it if you don't plan for that in advance.

    How are customer service and technical support?

    Databricks technical support is excellent. They provided their responses on time, and they're useful. However, I don't have extensive experience with them.

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

    I have used different Microsoft solutions before.

    How was the initial setup?

    The initial setup depends on the readiness of the team working with Databricks. There is no one template saying that it's easy, and it isn't easy. It can be complex to set up if you don't have a really good plan.

    You can get in this environment at least for a test. You can do it in the lab, follow it step by step, and that'll take about an hour. The difficulty depends on the business requirements. 

    If it's for training purposes, you can do it in about half an hour, and you're good to go. If you need it to support a business, it will be much more rigorous because multiple divisions would be interested in running their own environment, working with their data.

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

    The price is okay. It's competitive. 

    What other advice do I have?

    If you're thinking of implementing Databricks, I would recommend working with professionals. It'll help you save time. Also, plan the work and work the plan. Otherwise, it'll be a waste of time and money.

    On a scale from one to ten, I would give Databricks a nine.

    Which deployment model are you using for this solution?

    Public Cloud
    Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
    Oscar Estorach - PeerSpot reviewer
    Chief Data-strategist and Director at theworkshop.es
    Real User
    Top 5Leaderboard
    Flexible, stable, and reasonably priced
    Pros and Cons
    • "The solution is very easy to use."
    • "The integration of data could be a bit better."

    What is our primary use case?

    We primarily use the solution for retail and manufacturing companies. It allows us to build data lakes.

    What is most valuable?

    The solution is very easy to use. 

    The storage on offer is very good. 

    The solution is perfect for dealing with big data.

    The artificial intelligence on offer is very good.

    The product is quite flexible.

    We have found the solution to be stable. 

    The cloud services on offer are very reasonably priced.

    Technical support is very good. They also have very good documentation on offer to help you navigate the product and learn about its offerings. 

    What needs improvement?

    The solution works very well for us. I can't recall any missing features or anything the solution really lacks. It's very complete. 

    It would help if there were different versions of the solution on offer.

    The integration of data could be a bit better.

    For how long have I used the solution?

    I've worked for about 20 to 25 years in business intelligence analytics and have worked with Databricks for about four years at this point. 

    What do I think about the stability of the solution?

    The stability of the solution is very good. It doesn't crash or freeze. There are no bugs or glitches. Its performance is very good.

    What do I think about the scalability of the solution?

    The scalability is quite good. A company that needs to expand it can do so with ease.

    We only have four people on the solution at this time. The front-end users never use the product directly. The companies aren't that big here. If the economy improves, we'll likely have more of a need for the product.

    How are customer service and technical support?

    I've dealt with technical support in the past and have found them to be very good. They are helpful and responsive. We are satisfied with their level of service.

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

    I work with  Databricks, Cloudera and Snowflake.

    How was the initial setup?

    The solution is on the cloud and therefore there isn't really an installation process that you need to go through. You only really need to configure the clusters. 

    Within the clusters, you configure according to how many platforms you need, or if you want to, you can build a cluster for artificial intelligence. You just configure it as required. 

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

    The pricing of the product is very reasonable. The fact that it is on the cloud makes it a less expensive option. Other solutions that are on-premises are quite expensive.

    What other advice do I have?

    We are customers and end-users. 

    Databricks is on the could and therefore, we're always on the latest version of the solution. It's constantly updated for us so that we have access to the latest updates and upgrades. 

    I'd rate the solution at a nine out of ten. The capability of the product is quite good and we are very satisfied with it overall. 

    I'd recommend the solution to other companies and organizations.

    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?

    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    Head of Referential and Big Data at a financial services firm with 5,001-10,000 employees
    Real User
    A highly scalable unified data platform that provides data access to any type of user
    Pros and Cons
    • "I like cloud scalability and data access for any type of user."
    • "It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."

    What is our primary use case?

    We use Databricks to define tool data and have many use cases to analyze and distribute the data.

    How has it helped my organization?

    Data is open to everyone; they can access it through many channels, including notebooks or SQL. That on its own democratizes the data.

    What is most valuable?

    I like cloud scalability and data access for any type of user.

    What needs improvement?

    It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow.

    In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them.

    For how long have I used the solution?

    I have been using Databricks for roughly one and a half years.

    What do I think about the stability of the solution?

    Stability is excellent.

    What do I think about the scalability of the solution?

    Databricks is scalable. You can use the power of the cloud to scale your cluster size, either CPU or memory. The data doesn't work like a standard database, so you don't have it based on files, and you don't copy the data. It's super scalable. It's only the computing that you have to scale with the data.

    We probably have 40 users with roles like developers, business analysts, and data scientists. We have big plans to increase the usage and have more departments using it.

    How are customer service and support?

    Technical support has helped us.

    On a scale from one to ten, I would give technical support a five.

    How would you rate customer service and support?

    Positive

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

    We used Cloudera before switching to Databricks.

    How was the initial setup?

    The initial setup was fairly okay. It takes about two minutes to deploy this solution. It's all code, so we click a button, and then it's done.

    On a scale from one to five, I would give the initial setup a four.

    What about the implementation team?

    We set up and deployed this solution.

    What was our ROI?

    On a scale from one to five, I would give our ROI a three.

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

    We only pay for the Azure compute behind the solution. If you want to compute, you have to have a database layer and Azure below.

    On a scale from one to five, I would give their pricing a two.

    Which other solutions did I evaluate?

    We looked at other options such as Snowflake and Cloudera on the cloud,

    What other advice do I have?

    I would tell potential users that they need proper cloud engineers and a 
    cloud infrastructure team to use this solution.

    On a scale from one to ten, I would give Databricks a nine.

    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?

    Microsoft Azure
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
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    Updated: June 2022
    Buyer's Guide
    Download our free Databricks Report and get advice and tips from experienced pros sharing their opinions.