

Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse.
When it comes to big data processing, I prefer Databricks over other solutions.
For a lot of different tasks, including machine learning, it is a nice solution.
The enterprise subscription offers more benefits, ensuring valuable outcomes.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
I rate the technical support as fine because they have levels of technical support available, especially partners who get really good support from Databricks on new features.
They provide callbacks to ensure clarity and resolution of any queries.
Databricks is an easily scalable platform.
I would rate the scalability of this solution as very high, about nine out of ten.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is definitely a very stable product and reliable.
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.
SAS Visual Analytics is stable and manages data effectively without crashing.
It would be beneficial to have utilities where code snippets are readily available.
They're now coming up with their IBI dashboard, and I think they're on the right track to improve that even further.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI.
It is not a cheap solution.
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
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 ability to query information from our Excel data into SAS to view specific data is invaluable.
| Product | Market Share (%) |
|---|---|
| Databricks | 8.3% |
| Snowflake | 17.7% |
| Dremio | 8.9% |
| Other | 65.1% |
| Product | Market Share (%) |
|---|---|
| SAS Visual Analytics | 3.4% |
| Tableau Enterprise | 19.2% |
| Apache Superset | 9.2% |
| Other | 68.2% |


| Company Size | Count |
|---|---|
| Small Business | 25 |
| Midsize Enterprise | 12 |
| Large Enterprise | 56 |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 8 |
| Large Enterprise | 19 |
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?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.
SAS Visual Analytics is a data visualization tool that is used for reporting, data exploration, and analytics. The solution enables users - even those without advanced analytical skills - to understand and examine patterns, trends, and relationships in data. SAS Visual Analytics makes it easy to create and share reports and dashboards that monitor business performance. By using the solution, users can handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. SAS Visual Analytics is most suitable for larger companies with complex needs.
SAS Visual Analytics Features
SAS Visual Analytics has many valuable key features. Some of the most useful ones include:
SAS Visual Analytics Benefits
There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the SAS Visual Analytics solution.
A Senior Manager at a consultancy says, “The solution is very stable. The scalability is good. The usability is quite good. It's quite easy to learn and to progress with SAS from an end-user perspective.
PeerSpot user Robert H., Co-owner at Hecht und Heck GmbH, comments, “What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes.
Andrea D., Chief Technical Officer at Value Partners, explains, “The best feature is that SAS is not a single BI tool. Rather, it is part of an ecosystem of tools, such as tools that help a user to develop artificial intelligence, algorithms, and so on. SAS is an ecosystem. It's an ecosystem of products. We've found the product to be stable and reliable. The scalability is good.”
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