Amazon EMR is a cloud-native big data platform for processing vast amounts of data quickly, at scale. Using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi (Incubating), and Presto, coupled with the scalability of Amazon EC2 and scalable storage of Amazon S3, EMR gives analytical teams the engines and elasticity to run Petabyte-scale analysis.
N/A
Databricks Lakehouse Platform
Score 8.3 out of 10
N/A
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…
$0.07
Per DBU
Pricing
Amazon EMR (Elastic MapReduce)
Databricks Lakehouse Platform
Editions & Modules
No answers on this topic
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
Offerings
Pricing Offerings
Amazon EMR
Databricks Lakehouse Platform
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Amazon EMR (Elastic MapReduce)
Databricks Lakehouse Platform
Considered Both Products
Amazon EMR
Verified User
Analyst
Chose Amazon EMR (Elastic MapReduce)
Compared to Databricks, Amazon EMR is a much cheaper option to get the work down. And compared to Amazon ec2, Amazon EMR is a much more powerful tool to get large datasets transformation down in a fairly short amount of time. The drawback is that amazon EMR would be very costly …
Director of Customer Operations & Account Management
Chose Amazon EMR (Elastic MapReduce)
EMR is more suited for developers. Databricks feel more for data science-oriented with its notebooks and customs visualizations. With EMR you can more easily add additional capacity on-damnd on the instance. With others is a more cumbersome process. And then, you can also …
The alternatives to EMR are mainly hadoop distributions owned by the 3 companies above. I have not used the other distributions so it is difficult to comment, but the general tradeoff is, at the cost of a longer setup time and more infra management, you get more flexible …
Having one of these enterprise edition license comes at its own costs. But, the flexibility to have the cluster spin up with the workbenches and code snippets on the same is really beneficial. Especially, if one had to move out of EMR and consider an option which reduces the …
The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when …