The use case for Databricks is that we use the clustering for high big data processing within the cluster.
Databricks Data Intelligence Platform
Databricks, Inc.External reviews
637 reviews
from
and
External reviews are not included in the AWS star rating for the product.
Unity Catalog streamlines efficiency, despite Compute mode limitations
What do you like best about the product?
The Unity Catalog bundles useful data types together like Tables (delta), Models, Views, Functions and Volumes (for unstructured data). Additionally, the Workflows tab streamlines efficiency to run jobs and pipelines updating and engaging with big data.
What do you dislike about the product?
The worst functionality comes with the compute modes, and the restricted abilities. For example, Dedicated single-user access mode is essential to utilize ML runtimes and some Spark context access; however, Standard shared access mode is key for the latest UC functionality such as engaging with Shallow Clones properly.
What problems is the product solving and how is that benefiting you?
Problems with managing big data and streamlining execution time while also managing permissions and governance are all problems that are efficiently solved using Databricks Data Intelligence Platform and Unity Catalog.
Databricks review
What do you like best about the product?
Most helpful is the UI ans assistant. It helps a lot
What do you dislike about the product?
Least helpful is the workflow UI . It does not help
What problems is the product solving and how is that benefiting you?
It helps break silos of my data.
All in one place for all data needs
What do you like best about the product?
Honestly, it’s how it turns the chaos of raw data into something beautifully orchestrated—like jazz, but with less saxophone and more Spark.
I love that it’s not just a tool—it’s an entire ecosystem. It brings data engineering, analytics, and AI into one unified environment. That means I don’t have to duct tape a dozen tools together just to move a pipeline forward. Fewer silos, more flow. And the fact that it’s built on open standards like Delta Lake and Apache Spark? Chef’s kiss.
The collaborative features are also huge. Being able to work seamlessly across teams in notebooks, share insights, and iterate in real time? It’s like Google Docs for data nerds, but smarter and with fewer formatting headaches.
Oh, and Unity Catalog? Game-changer. It gives me visibility and governance without making me feel like I need a second job in security.
So yeah—what I like most is that it makes doing complex things feel, well… less complex. It’s not just about managing data—it’s about getting real intelligence out of it, fast. And that’s exactly the kind of velocity I like.
I love that it’s not just a tool—it’s an entire ecosystem. It brings data engineering, analytics, and AI into one unified environment. That means I don’t have to duct tape a dozen tools together just to move a pipeline forward. Fewer silos, more flow. And the fact that it’s built on open standards like Delta Lake and Apache Spark? Chef’s kiss.
The collaborative features are also huge. Being able to work seamlessly across teams in notebooks, share insights, and iterate in real time? It’s like Google Docs for data nerds, but smarter and with fewer formatting headaches.
Oh, and Unity Catalog? Game-changer. It gives me visibility and governance without making me feel like I need a second job in security.
So yeah—what I like most is that it makes doing complex things feel, well… less complex. It’s not just about managing data—it’s about getting real intelligence out of it, fast. And that’s exactly the kind of velocity I like.
What do you dislike about the product?
First off, pricing transparency can be… let’s call it “mysterious.” You think you’re just running a simple job, and then BAM—surprise costs like it’s your birthday, but the gifts are all invoices. I’d love a bit more clarity and control there, especially when you’re trying to scale responsibly.
What problems is the product solving and how is that benefiting you?
Certificate related parsing with great speed
The best analytical and data governing platform
What do you like best about the product?
The best I like about snaplogic is while doing data transformation of datasets in notebooks it has many languages to use like sql,pyspark and R. This enable me to use any language and effectively complete my requirements.data bricks has many features like Ai,unity catalog workflow managements which makes my ETL implementation ,and data integration easy and quick
What do you dislike about the product?
Under heavy usage the UI responsive for some implementations like job tracking ,Notebook versioning is a bit slugguish on web
What problems is the product solving and how is that benefiting you?
The problems databricks solving is effective datasets to data product creation satisfying business requirements
A effective data governing platform
What do you like best about the product?
The best about databricks is its delta warehousing which makes ETL process faster and effective.And also unity catalog feature which centralize data governance easy and also the data bricks ai assistant which makes data transformations easy and automated ,the customer support is helpful and quick.
What do you dislike about the product?
the only thing i dislike is it does not support RDD in pyspark codes.
What problems is the product solving and how is that benefiting you?
Data bricks is useful in solving workflows managing/constructing and data transformations serving business requirements. Benefiting me with daily transformations and workflows processing
Experiencing smooth performance and cost advantages over previous tools
What is our primary use case?
What is most valuable?
I think it is difficult to determine which feature of Databricks I enjoy the most since there are many valuable features.
What's valuable about Databricks to my organization is that it is more cost-effective and provides better performance than the current AWS tools and services they offer.
What needs improvement?
I am uncertain about specific improvements for Databricks.
It would be beneficial to make Databricks even more cost-effective.
For how long have I used the solution?
I have been using Databricks for two years.
What do I think about the stability of the solution?
My experience with Databricks has been smooth, and I haven't encountered any issues.
Databricks is definitely a very stable product and reliable.
How are customer service and support?
I have not used Databricks customer service or support.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Before Databricks, I used Batch processing, Fargate, and possibly Kubernetes.
I switched from my previous solutions because they were either too expensive or too difficult to configure.
Which other solutions did I evaluate?
I have considered other solutions besides Databricks, such as Snowflake, but we haven't explored it extensively yet.
We are still early in our Snowflake experience, so we don't know the pros and cons compared to Databricks.
What other advice do I have?
My deployment model for Databricks is limited as I'm not a heavy user.
I am not the person who purchased Databricks, but it was possibly acquired through the AWS Marketplace.
I may not have utilized Databricks machine learning capabilities.
My experience with the pricing and licensing model is that it remains relatively expensive. Though it's less expensive than AWS, we still need a more cost-effective solution.
I would rate Databricks overall a nine out of ten.
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Databricks makes Teamwork Data Super Easy
What do you like best about the product?
I like Databricks because it helps everyone work together on big data projects in one place. It’s easy to share ideas, do smart computer stuff, and understand lots of information as a team.
What do you dislike about the product?
Sometimes, it’s hard to move our old data into Databricks. If you are not used to it, learning everything can feel tricky at first.
What problems is the product solving and how is that benefiting you?
Databricks brings all our data together, making teamwork easier and helping us make smart decisions faster.
Databricks simplify data work and scale effortlessly !
What do you like best about the product?
What I really like about Databricks is how it brings every technical requirements under one space like kind one stop place for anything related to data. From cleaning and organizing to building machine learning models, it makes the whole process less messy. We could work as a team without constantly emailing or switching tools. Performance wise, it holds up even when we throw big workloads at it, and it connects well with other tools we use. Real-time data processing is smooth, and I’ve noticed we get insights much faster now. It’s also got solid controls around data access and tracking, which gives peace of mind on the security side. Overall, it's a smart, efficient platform that makes working with data feel way more natural.
What do you dislike about the product?
Databricks offers a good environment for data processing and analytics, but it does come with its set of challenges. One of the primary challenge is the learning curve, especially for those new to big data tools.But customer support really try their best.
What problems is the product solving and how is that benefiting you?
One thing I’ve noticed using Databricks is how much it cuts down on the usual complexity of big data work. Whether it's handling streaming feeds or batch jobs, it takes care of both in the same place, which saves time and confusion. We didn’t have to deal with a lot of setup or infrastructure headaches , things just scale up when needed, and performance stays solid even with heavier loads. It’s kind of like having a behind the scenes crew managing the technical weight so we can focus on the actual data insights. Makes life easier for the whole team.
Excellent integration with ML libraries and real time pipelines.
What do you like best about the product?
Predictive model for early hospital readmission risk detection was developed by our firm. We were processing sensitive health records using Databricks because security and compliance were our top priorities. Databricks support for HIPAA compliance and secure workspace management made it a trustworthy platform to host patient datasets. Using Delta Lake we handed the millions of records with the reliable performance. The integration with pandas and MLflow within notebook was also seamless. I especially appreciate the real time dashboard we build for a hospital admin staff to view live model prediction and alerts.
What do you dislike about the product?
During this project one of the biggest challenge we faced was setting up real time data streaming with HL7 format via Kafka into Databricks. While Databricks does support auto loaders but we had to write a fair amount of custom logic to parse and validate complex healthcare specific schemas
What problems is the product solving and how is that benefiting you?
We have seen improved collaboration across hospitals since each can now securely access insights and contribute feedback via shared notebooks and dashboards. Databricks has become the central nervous system for this project.
Future of Data Intelligence for Businesses
What do you like best about the product?
The built in visual tools help us understand data more easily. Instead of just seeing a bunch of numbers, I can spot trends and patterns clearly, which makes it easier to make smart decisions.
What do you dislike about the product?
Because it’s a cloud based platform, everytime I need a stable internet connection to use it. Sometime I am working offline or in places with spotty internet.
What problems is the product solving and how is that benefiting you?
I am really happy with how Databricks has transformed our data processes. It’s made things faster, simpler and more efficient which allowing to focus on insights rather than struggling with infrastructure.
showing 51 - 60