I use Databricks for various purposes, including data engineering, MLOps, machine learning training and deployment, the entire ML cycle, and dashboards. It serves different purposes for different projects.
Databricks Data Intelligence Platform
Databricks, Inc.External reviews
640 reviews
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External reviews are not included in the AWS star rating for the product.
Top-class Data Management Platform
What do you like best about the product?
The single word I can say about Data bricks is they have really top class services in the field of data management. Their platform have power to handle huge data with very simple modules without any extra integrations. The services we are using from Data bricks gives freedom to handle data on every single steps.
What do you dislike about the product?
Whenever we need to store data and analyze the data we use Data bricks analytical views for that and their really gives best insights from the data.
What problems is the product solving and how is that benefiting you?
Mainly I used Data bricks only for warehousing and Data Analytics and really I have very satisfying experience with that. Their team reply quickly and solve the query om immediate basis if we have any. Overall, I recommend Data bricks with my social groups also for referring to use for data management.
Databricks has opened a world of possibilities for me
What do you like best about the product?
Databricks is a tool that is constantly evolving. I really appreciate the number of features they release, and the fact that they are up to date. It's an everyday platform that adapts to all use cases and is easy to integrate. It's an all-in-one solution with ETL with warehouses, Python, Spark, Scala, machine learning, and GenAI.
What do you dislike about the product?
Sometimes I wish they would update the documentation more, that there weren't so many changes in the API .
The release notes of the changes were better explained to us and that we would have time to address the changes.
Customer support is one thing that they have to improve too
The release notes of the changes were better explained to us and that we would have time to address the changes.
Customer support is one thing that they have to improve too
What problems is the product solving and how is that benefiting you?
With Unity Catalog we have been able to address many issues we had with the previous integration with Glue and AWS, now everything is simpler and we can have more granularity in our security and ease in our processes.
Powerful solution with user friendly Data analytics
What do you like best about the product?
The most likelihood part about Data bricks is for me their user friendly data analytical user dashboards that gives really great user experience to visualize the data on multiple patterns without getting error.
What do you dislike about the product?
They have lots of integration option that implement very effective result on data governance and data analyzing. The customer support team also are very quick and responsive to revert back with resolution.
What problems is the product solving and how is that benefiting you?
Overall, They have Data warehouse, data analytical dashboard and data governance option at one platform. Data bricks make our work more smoother and easy to operate that gives more effective result to create insights from data.
Best unified platform for AI and data analytics
What do you like best about the product?
It stands out as it seamlessly integrates data engineering, analytics and AI/ML workloads. Their Lakehouse architecture is a game changer as it combines the best of data lakes and warehouse, eliminating then need for complex ETL pipelines.
What do you dislike about the product?
Cluster startup is slow and time consuming. Price of products are very high if it is not used to its fully utilizing capabilities.
What problems is the product solving and how is that benefiting you?
We use for big data processing and real time analytics and AI driven insights. It has significantly improved data governance, performance and collaboration across teams. By replacing our legacy ETL workflow we have reduced processing time by half and improved model deployment efficiency.
The Tool for data analysis is Phenomenal
What do you like best about the product?
It offers interactive notebooks where different users can collaborate on data projects in real time.
What do you dislike about the product?
The disadvantage is that depending on the cluster, it takes a long time to pull the database.
What problems is the product solving and how is that benefiting you?
Help to process large volumes of data, understand and optimize problems, because through analysis we can make more assertive decisions.
Databricks -Data transformation and pipeline Use
What do you like best about the product?
Databricks is very user friendly platform whuch supports multiple database and scripting languages at same place.
Pyspark and delta feature enhance the speed of data extraction
AI assostant auto complete the code and optimize when needed to do that.
Lots of paid connectors are available to use.
Pyspark and delta feature enhance the speed of data extraction
AI assostant auto complete the code and optimize when needed to do that.
Lots of paid connectors are available to use.
What do you dislike about the product?
Transformation from sql to pandas can be very time consuming.
Estimated runtime should be available so use can optimize the pipeline or notebook.
Estimated runtime should be available so use can optimize the pipeline or notebook.
What problems is the product solving and how is that benefiting you?
Simple platform to transform or aggrefate the data to create business data views/table.
Simultaneous data flow management.
What do you like best about the product?
- It has an excellent connection with the MLFlow system which guarantees that our clients have access to creation, management, monitoring and progress in Machine Learning.
- It offers professional processes to manage the clients infrastructure and manage all the clusters, all this can be done from the cloud and saves time in collecting data from the clusters.
- We can link several data sources perfectly and simultaneously, this helps collect all the data of our clients in a safe and automated manner, without going through complex data registration process, we can collect a large volume of data easily.
- It offers professional processes to manage the clients infrastructure and manage all the clusters, all this can be done from the cloud and saves time in collecting data from the clusters.
- We can link several data sources perfectly and simultaneously, this helps collect all the data of our clients in a safe and automated manner, without going through complex data registration process, we can collect a large volume of data easily.
What do you dislike about the product?
Databricks never gave us any type of negative experience, at all times it was able to offer management, data storage and collection of large volumes of data. With Databricks, our MSP-type functions have improved and have never had any failures collecting all the data of our clients who access IT services.
What problems is the product solving and how is that benefiting you?
Databricks has allowed the data management of our entire company to be much more proportional, allowing us to work together and integrate this platform with various Apache and ML services. This platform has benefited me a lot, because it has allowed us to completely analyze the data and collecting a large volume of data and storing it in the cloud, collecting data from our clients and managing this data together and working together, has never been easier until it came to this platform. I'm satisfied with the results, since it has benefited data management in our MSP company.
Databricks is The data and AI company
What do you like best about the product?
Databricks lakehouse platform is unique in 3 ways-
Simple- Data only needs to exist once to support all your workloads.
Open- It is based on open standards to work with existing tools and avoid propritary formats.
Collaborative - DE, Analysts and DS can work together much more easily.
Simple- Data only needs to exist once to support all your workloads.
Open- It is based on open standards to work with existing tools and avoid propritary formats.
Collaborative - DE, Analysts and DS can work together much more easily.
What do you dislike about the product?
Speed of innovations and features released. Sometimes features rolled-out without enough support and documentations.
What problems is the product solving and how is that benefiting you?
It is helping us in many ways:
1) Faster data processing with optimized features provided via DBR which is additional performace incentives on top of open spark e.g. Dynamic file pruning, low shuffle merge, deletion vectors, AQE etc
2) Unified governance and security - Rise of multi cloud adoption where each cloud has a unique governance model that requires individual familiarty intoduce complexity. solutions are unity catalog and data sharing. It is helping us a lot providing centralized governance
1) Faster data processing with optimized features provided via DBR which is additional performace incentives on top of open spark e.g. Dynamic file pruning, low shuffle merge, deletion vectors, AQE etc
2) Unified governance and security - Rise of multi cloud adoption where each cloud has a unique governance model that requires individual familiarty intoduce complexity. solutions are unity catalog and data sharing. It is helping us a lot providing centralized governance
Unlocking Data Potential: A Comprehensive Review of the Databricks Data Intelligence Platform
What do you like best about the product?
I like how Databricks seamlessly integrates data engineering, science and machine learning, offering scalabilty, collaboration and efficient analytics in one platform.
What do you dislike about the product?
The main drawbacks of Databricks are its steep learning curve and complex pricing, which can be challenging for new users or smaller teams or organizations with limited budgets.
What problems is the product solving and how is that benefiting you?
Databricks solves problems releated to data processing at scale, simplifying the integration of data engineering, data science and machine learning workflows. it allows for faster data analysis, more efficient model building, and seamless collaboration across teams.
Unified platform simplifies end-to-end processes with intuitive data access solutions
What is our primary use case?
What is most valuable?
Unity Catalog is a feature I am currently using extensively. I am migrating many projects to Unity Catalog. MLflow, which I use for model registering and creating the lineage of models, is also valuable.
Additionally, Databricks serves as a single platform for conducting the entire end-to-end lifecycle of machine learning models or AI ops. I don't need to switch between various tools, making it an all-encompassing solution for development and research. I use the lake house and utilize features effectively.
What needs improvement?
There has been a significant evolution in databases. One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files. Standardization of file paths on the system could help, as engineers sometimes struggle.
It would be beneficial to have utilities where code snippets are readily available. This would allow engineers to easily click a snippet and import it into the notebook, enabling quick modifications to variables or paths for fetching files, such as reading data from DBFS files. If I could right-click to copy absolute paths or to read files directly into a data frame, it would standardize and simplify the process.
For how long have I used the solution?
I have used the solution for five years plus.
What do I think about the stability of the solution?
I would rate stability seven to eight out of ten.
What do I think about the scalability of the solution?
I would rate scalability seven to eight out of ten.
How are customer service and support?
I do not have any issues that require support. Many resources are available online.
How would you rate customer service and support?
Neutral
How was the initial setup?
I use infrastructure as code on the cloud to deploy the infrastructure. I have all the Git repositories and code repositories for deploying the code and models in the workspace. My setup includes a shared workspace, shared clusters, and integration with Unity Catalog.
What about the implementation team?
I have a team of 100 engineers working with me, and I head the Center of Excellence (COE).
What was our ROI?
I believe it is competitive across clouds. When it comes to big data processing, I prefer Databricks over other solutions. Cost-wise, it is very competitive. The setup process is straightforward, thanks to the use of Spark clusters. This allows for faster turnaround times with Databricks.
What other advice do I have?
The product rating is nine out of ten.
Databricks serves as a single platform that can handle numerous end-to-end machine learning tasks. The configuration is simple, scalability is excellent, and monitoring cluster utilization facilitates informed business decisions.
It's easy to schedule jobs, pipelines, and handle multiple use cases in parallel, providing countless benefits.
Which deployment model are you using for this solution?
Hybrid Cloud
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