Databricks Valuable Features
Lead Data Architect at a government with 1,001-5,000 employees
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.View full review »
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.View full review »
Chief Risk Officer at Cegid Invoice and Financing
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.View full review »
Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions.View full review »
Head of Data & Analytics at a tech services company with 11-50 employees
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.View full review »
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.View full review »
Head of Referential and Big Data at a financial services firm with 5,001-10,000 employees
I like cloud scalability and data access for any type of user.View full review »
Databricks gives you the flexibility of using several programming languages independently or in combination to build models.
The quick visualization of the data is very good.
The workload management functionality works well.View full review »
Databricks lets you schedule jobs pretty easily, and you can use SQL, Spark SQL, Python, or R. It also allows you to save a table or view.
I like that you can connect to multiple data sources. Most of our data is stored in the Azure data lake, but my previous company connected to SQL databases or even blob storage.
They've improved on many features. I don't do data engineering, but I had an issue a couple of years ago at my two companies ago. It took a long time to read and save tables, but I think the new Delta feature helped.
I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature.View full review »
The solution is built from Spark and has integration with MLflow, which is important for our use case.
Databricks is also user-friendly, providing customizable codes and models that allow people to experiment quickly.
Integration of Delta Lake is another useful feature.View full review »
Data Scientist at a retailer with 5,001-10,000 employees
One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often. You can just spin it off and use that for a lot of your pre-processing, which is very convenient.
The normal features are very good in terms of doing some quick development or doing some EDA.
Also, one of the newest features brought into this solution provides you with a way to solve, deploy, and train models using the platform itself. Or, it can connect to your Azure Machine Learning in order to train, deploy, and productionalize some of the machine learning models.View full review »
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.View full review »
Chief Research Officer at a consumer goods company with 1,001-5,000 employees
I think the features I like the most are the scalability of the solution as well as its ability to share. 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.View full review »
The ability to stream data and the windowing feature are valuable. There are a number of targeted integration points, so that is a difference between Stream Analytics and Databricks. The integrations input or output are better in Databricks. It's accessible to use any of the Python or even Java. I can use the third party, deploy it, and use it.View full review »
Senior Data Engineer at TCS
Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily.View full review »
Databricks can cut across the entire ecosystem of open source technology which gives an extra level in terms of getting the transformatory process of the data. The solution is primarily open source and they have bolstered its components to make it more fit for purpose for a complete Azure Data platform. The solution is responsible for the core transformatory activities. While Azure Data Factory is very good for pulling in the data, doing the basic standardization and profiling, Databricks is more about making fundamental changes in structure or in size of the data and aligning it for subsequent consumption, or for the final layer on Synapse. It also has the power to complement and work with Spark and elements related to Python.View full review »
Chief Data Scientist at a tech services company with 11-50 employees
Databricks integrates well with other solutions.View full review »
Associate Manager at a consultancy with 501-1,000 employees
The main features of the solution are efficiency.
We were trying to process 300 million records over 10 years. If you are processing that high number of records through the ADF pipeline with, for example, Azure, it took approximately six hours. In order to reduce the burden on our ADF pipeline, we wrote a simple code in this solution where we can read and write to the file into the temporary Storage Explorer. By going through this solution, we were able to complete the processing of the data in half an hour.
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.View full review »
Data Architect at a tech services company with 201-500 employees
The fast data loading process and data storage capabilities are great.
Based on the data loads and the performance, you can easily scale up the clusters.View full review »
Data Science Lead at a mining and metals company with 10,001+ employees
The scalability brings value to this solution.
It can send out large data amounts.View full review »
Advanced Analytics Lead at a pharma/biotech company with 1,001-5,000 employees
The solution is easy to use and has a quick start-up time due to being on the cloud.View full review »
Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client.View full review »
I think what I value is more about the technology itself because you don't need to have too much knowledge to be able to use the solution.View full review »
Technical Architect at a tech services company with 10,001+ employees
I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job. So you can create a robust solution by working together with other professionals.View full review »
Big Data and Cloud Architect at a computer software company with 201-500 employees
Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good.View full review »
Business Development Specialist at a tech services company with 51-200 employees
Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution.View full review »