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This reduction in both time and money resulted in real-time impact and significant cost savings.
For a lot of different tasks, including machine learning, it is a nice solution.
When it comes to big data processing, I prefer Databricks over other solutions.
I have seen a return on investment with VMware Tanzu Data Solutions because of its speed and the robustness of the environment.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
I would give Databricks customer support a rating of ten.
If anything happens in terms of technicalities and I raise a ticket, they address it immediately, irrespective of the SLA agreement.
I am going to give them a ten out of ten.
Customer support for VMware Tanzu Data Solutions has been good with me and with VMware, including Broadcasts.
The sky's the limit with Databricks.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is an easily scalable platform.
Most of our functions or jobs are queued due to that.
They release patches that sometimes break our code.
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
Databricks is definitely a very stable product and reliable.
I have faced stability issues, mainly due to the storage my organization has, though I am not sure if it's specifically due to the tool.
Broadcom and VMware are doing a great job. They are fast in response.
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
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 use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
Simplifying the initial setup and day-to-day operations could reduce the learning curve for new users.
They are losing business.
I think they must ensure compatibility with many cloud technologies, including those from the US and China, to make it more versatile in the future.
It is not a cheap solution.
I believe that in terms of credits for Databricks, we're spending between £15,000 and £20,000 a month.
My experience with pricing, implementation costs, and licensing is that it is very efficient and very fast.
My experience with pricing, setup cost, and licensing for VMware Tanzu Data Solutions is that it is a bit expensive.
Databricks' capability to process data in parallel enhances data processing speed.
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
The principal aspect is the creation of Kubernetes clusters.
Kubernetes native application databases that are managed together allow scaling of application, database, storage, and networking to be automated.
The self-healing feature of VMware Tanzu Data Solutions has helped my team by recreating new instances automatically when particular instances are in a failure state, thereby maintaining the complete environment and reducing downtime.


| Company Size | Count |
|---|---|
| Small Business | 26 |
| Midsize Enterprise | 12 |
| Large Enterprise | 60 |
| Company Size | Count |
|---|---|
| Small Business | 32 |
| Midsize Enterprise | 11 |
| Large Enterprise | 52 |
Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.
Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.
What features make Databricks unique?
What benefits can users expect from Databricks?
In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.
VMware Tanzu is a robust platform tailored for data warehousing, complex analytics, BI applications, and predictive analytics. It excels in scalability, performance, and parallel processing, enhancing data handling efficiency. Users report significant productivity improvements and streamlined operations, making it ideal for comprehensive data solutions.
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