We performed a comparison between Amazon EMR and Dremio based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The initial setup is straightforward."
"When we grade big jobs from on-prem to the cloud, we do it in EMR with Spark."
"The solution is scalable."
"The solution helps us manage huge volumes of data."
"Amazon EMR's most valuable features are processing speed and data storage capacity."
"It has a variety of options and support systems."
"We are using applications, such as Splunk, Livy, Hadoop, and Spark. We are using all of these applications in Amazon EMR and they're helping us a lot."
"The solution is pretty simple to set up."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Dremio allows querying the files I have on my block storage or object storage."
"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 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."
"We primarily use Dremio to create a data framework and a data queue."
"Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana."
"The product's features for storing data in static clusters could be better."
"We don't have much control. If we have multiple users, if they want to scale up, the cost will go and increase and we don't know how we can restrict that price part."
"As people are shifting from legacy solutions to other technologies, Amazon EMR needs to add more features that give more flexibility in managing user data."
"Amazon EMR can improve by adding some features, such as megastore services and HiveServer2. Additionally, the user interface could be better, similar to what Apache service provides, cross-platform services."
"There were times where they would release new versions and it seemed to end up breaking old versions, which is very strange."
"Modules and strategies should be better handled and notified early in advance."
"The problem for us is it starts very slow."
"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."
"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."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"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."
Amazon EMR is ranked 8th in Cloud Data Warehouse with 20 reviews while Dremio is ranked 11th in Cloud Data Warehouse with 6 reviews. Amazon EMR is rated 7.8, while Dremio is rated 8.6. The top reviewer of Amazon EMR writes "Provides efficient data processing features and has good scalability ". On the other hand, the top reviewer of Dremio writes "It enables you to manage changes more effectively than any other platform". Amazon EMR is most compared with Snowflake, Cloudera Distribution for Hadoop, Azure Data Factory, Amazon Redshift and Apache Spark, whereas Dremio is most compared with Databricks, Snowflake, Starburst Enterprise, Amazon Redshift and Microsoft Azure Synapse Analytics. See our Amazon EMR vs. Dremio report.
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We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
