We compared Databricks and Dremio based on our user's reviews in several parameters.
Databricks excels in seamless integration, advanced analytics, and collaborative capabilities, with positive feedback on customer service and pricing. In contrast, Dremio is praised for query performance, data virtualization, and scalability, with excellent customer service and cost-effective pricing. Areas for improvement in Databricks include data visualization and pricing flexibility, while Dremio users note issues with performance on complex queries, documentation, and support response times.
Features: Databricks excels in seamless integration, collaborative capabilities, and advanced analytics. In contrast, Dremio stands out for its impressive query performance, data virtualization, user-friendly interface, strong security features, and scalability for large datasets.
Pricing and ROI: Databricks and Dremio have received positive user feedback regarding pricing, setup cost, and licensing. Users found both products to have reasonable and competitive pricing. The setup cost for Databricks was reported to be straightforward, while Dremio's setup process was easy and without significant costs. Both products offer flexible licensing options to meet different user needs. Overall, users had a positive experience with pricing, setup cost, and licensing of both Databricks and Dremio., Users have reported positive outcomes and returns on investment when utilizing both Databricks and Dremio. However, Databricks is praised for its significant impact on increasing efficiency, productivity, and data analysis capabilities, while Dremio is favored for providing favorable returns on investment.
Room for Improvement: Databricks could improve its data visualization capabilities, monitoring and debugging tools, integration with external sources, documentation for beginners, and pricing flexibility. Dremio needs to enhance its user interface, performance with complex queries, documentation, embedding into other applications, and support availability.
Deployment and customer support: In terms of the duration required to establish a new tech solution, user reviews for Databricks and Dremio differ. Databricks reviews mention varying durations for deployment and setup, while Dremio reviews indicate different timeframes for these processes, emphasizing the importance of context., Databricks' customer service is praised for its efficiency, helpfulness, and promptness. The support team is proactive and maintains excellent communication. Dremio's customer service is highly praised for its promptness, efficiency, and resourcefulness. Users appreciate their top-notch and reliable support.
The summary above is based on 53 interviews we conducted recently with Databricks and Dremio users. To access the review's full transcripts, download our report.
"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"The solution is an impressive tool for data migration and integration."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"Databricks helps crunch petabytes of data in a very short period of time."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"It's easy to increase performance as required."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"Dremio allows querying the files I have on my block storage or object storage."
"We primarily use Dremio to create a data framework and a data queue."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Databricks could improve in some of its functionality."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."
"The product needs samples and templates to help invite users to see results and understand what the product can do."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"Databricks' technical support takes a while to respond and could be improved."
"I have seen better user interfaces, so that is something that can be improved."
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"It shows errors sometimes."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Dremio is ranked 9th in Data Science Platforms with 6 reviews. Databricks is rated 8.2, while Dremio is rated 8.6. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of Dremio writes "It enables you to manage changes more effectively than any other platform". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Azure Stream Analytics, whereas Dremio is most compared with Snowflake, Starburst Enterprise, Amazon Redshift, Microsoft Azure Synapse Analytics and Microsoft Power BI. See our Databricks vs. Dremio report.
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