Our primary use case is in our project; we are dealing with Duo Special Data, where we need a lot of computing resources. Here, the traditional warehouse cannot handle the amount of data we are using, and this is where Databricks comes into the picture.

Databricks Data Intelligence Platform
Databricks, Inc.External reviews
External reviews are not included in the AWS star rating for the product.
Very Powerful Tool
Apache Spark Power
Machine Learning Capabilities
Scalability and Elasticity
Data Integration and Connector
Unity Catalog and Data Governance
These are a few key points on what I like most about Databricks.
Dependency on Cloud Infrastructure
Limited Offline access
As of now, I can think of these points on what I dislike about Databricks Platform
Great Data Handling & Management platform.
Supports even the partially arranged/aligned data also.
Provides a way for better data handling and Management ( like Unified View, graphical view, and Comparision graphs ), which helps in better decision-making.
Pricing is high compared to similar tools in the market.
2) To integrate with AI and Machine Learning tools: Having the data in a unified way using this tool helps us to integrate with other devices ( But this required some high technical expertise)
Best all-in-one Data Platform environment
* Unity Catalog that provides colum-level lineage and a centralized access right management service
* Delta Live Table that provides easy to implement Data Quality control and monitoring
* Extensive CLIs that gives freedom in chosing your CI/CD platform
* Clusters policies that allows a better cost control
Its compatibility with infrastructure-as-code tools such as Terraform also allows us to easily reproduce our standards accross multiple instances.
The integration with Azure Active Directory also eases the adoption and Access Control of resources and data assets.
Unified Platform for Analytics & Data Science
Best implementation of Lakehouse Architecture
Processes tremendous data easily
What is our primary use case?
What is most valuable?
The processing capacity is tremendous in the database. We are dealing with Azure as storage, so we have not faced any challenges. And also the connectors to different data sources. Moreover, it is not a language-dependent tool. Therefore, development also takes place faster. It is one of the best features of Databricks.
What needs improvement?
There is room for improvement in the documentation of processes and how it works. I was trying to get one of the certifications, so I saw an area of improvement there.
For how long have I used the solution?
I have been using Databricks for eight to nine months.
What do I think about the stability of the solution?
It is a stable product for us. We didn't see any challenges.
What do I think about the scalability of the solution?
There are around 30 to 35 users in our organization.
How was the initial setup?
The initial setup was easy because the third-party team made the clusters for us.
What about the implementation team?
A third-party team enabled the cluster to make the setup easy for us.
What other advice do I have?
I would advise using it based on the use case because it easily handles big data. It is your go-to tool if you are dealing with massive data.
Overall, I would rate the solution a nine out of ten. The tool performs well in various use cases, availability of documentation online, and compatibility with big data systems like GCP, Azure, or AWS.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
comprehensive data management platform
Intuitive interface .
Advanced analytics tools
Streamlining Data Management: My Experience with Databricks Lakehouse Platform
Another advantage is the platform's scalability and flexibility, which allows organizations to handle large volumes of data and adjust to changing business needs. Databricks Lakehouse Platform also offers powerful analytics and machine learning capabilities that enable users to gain deeper insights and make data-driven decisions.
In addition, the platform provides collaborative features that allow teams to work together on data-related projects, facilitating knowledge sharing and improving productivity. The platform's security and compliance features also ensure that data is protected and meets regulatory requirements.
Overall, Databricks Lakehouse Platform is a powerful tool that offers many benefits to organizations, including unified data management, scalability, flexibility, analytics, machine learning, collaboration, and security.
Another problem that Databricks Lakehouse Platform solves is the difficulty of integrating different data management and analytics tools. By providing a unified platform for data management, analytics, and machine learning, Databricks Lakehouse Platform eliminates the need for multiple tools and simplifies the integration process.
Databricks Lakehouse Solved lot of things
We can use choose the storage that is the most beautiful thing.
We can use it for SQL engine as well
It has new query engine designs providing high-performance SQL execution on data lakes.
Databricks has been absolute productivity tool
There is no dark mode, hence have to use a white theme.
Sometimes your queries get pushed to long queues which takes a lot of time and can be little frustrating.
- Creating and testing data pipelines using notebooks with various language support.
- Quick, easy, and on-demand resource creation and termination.