
Databricks Data Intelligence Platform
Databricks, Inc.External reviews
External reviews are not included in the AWS star rating for the product.
Databricks compute user
Great summit
New to BI/AI but growing it in out AI space
It was fantastic got to meet many peers
• Brings data from multiple sources (structured, unstructured, streaming) into a unified platform for centralized access.
2. Slow Time to Insights
• Enables faster data processing with Spark, Delta Lake, and optimized workflows to accelerate decision-making.
3. Scalability Issues
• Handles growing data volumes and user loads efficiently with cloud-native, distributed compute.
Overall good
Cloud Data Governance
Cloud platform enables advanced collaboration but new SAP data feature could enhance its capabilities
What is our primary use case?
What is most valuable?
What needs improvement?
For how long have I used the solution?
What was my experience with deployment of the solution?
What do I think about the stability of the solution?
What do I think about the scalability of the solution?
How are customer service and support?
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
How was the initial setup?
What about the implementation team?
What was our ROI?
What's my experience with pricing, setup cost, and licensing?
Which other solutions did I evaluate?
What other advice do I have?
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Integrating engineering and learning, but cost challenges arise with cluster management
What is our primary use case?
I usually handle data ingestion and create warehouses. I also assist other teams, such as analytics, to create reports or perform other tasks.
What is most valuable?
Having one solution for everything, from data engineering to machine learning, is beneficial since everything comes under one hood.
What needs improvement?
We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller.
We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly. We need to stay in sync with the DVR versions, and migrations can pose challenges. For example, issues arose when we moved a cluster from a previous version to the latest one. We could use their job clusters, however, that increases costs, which is challenging for us as a startup. Maintaining this infrastructure can be a headache.
For how long have I used the solution?
I have worked at a couple of companies, not just the current one, and I have about 20 to 25 months of experience with Databricks.
What do I think about the stability of the solution?
They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions.
What do I think about the scalability of the solution?
The patches have sometimes caused issues leading to our jobs being paused for about six hours. Fortunately, nothing important is currently running on Databricks, however, if there were, it would be a significant issue.
How are customer service and support?
They are good. My company has a contract with them that includes good support. Whenever we reach out, they respond promptly.
How would you rate customer service and support?
Neutral
What was our ROI?
With the benefits we receive, the price is reasonable. However, it's important to have good use cases. If it's just for data ingestion, it might not be the best solution price-wise. For a lot of different tasks, including machine learning, it is a nice solution.
What other advice do I have?
I would rate the solution seven out of ten. That rating also depends on how we have the contract with Databricks.
It's still a solid and good rating. I work as a data engineer and Databricks engineer.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Powerful and Intuitive
Reduces Job time to perform ETL on the Data Tables.
Provides seamless integration capabilities, but the cluster management features need improvement
What is our primary use case?
We use the product as a data science platform that enables me to handle and analyze large datasets efficiently.
What is most valuable?
Databricks can switch easily between cloud providers, such as Azure and GCP. It allows seamless integration with various data platforms and cloud providers, facilitating better data handling and analysis.
What needs improvement?
The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms like Snowflake. The ease and speed of managing clusters can also be enhanced, especially when scaling up resources. They could add more advanced data storage solutions like Iceberg and Delta files.
For how long have I used the solution?
I have been using Databricks for approximately two years.
What do I think about the stability of the solution?
I rate the product stability a seven out of ten.
What do I think about the scalability of the solution?
I rate the product scalability an eight.
How are customer service and support?
The technical support services are good.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup was straightforward. However, configuring policies could have been simpler.
What's my experience with pricing, setup cost, and licensing?
The product pricing is moderate.
Which other solutions did I evaluate?
I evaluated other options, including Snowflake, before choosing Databricks.
What other advice do I have?
Databricks is a robust solution for big data processing, offering flexibility and powerful features. While there are areas for improvement, especially in performance and cluster management, it remains a highly valuable tool in my data science toolkit.
I rate it a seven.