We performed a comparison between Amazon EMR and AWS Lake Formation 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 solution helps us manage huge volumes of data."
"The ability to resize the cluster is what really makes it stand out over other Hadoop and big data solutions."
"When we grade big jobs from on-prem to the cloud, we do it in EMR with Spark."
"It allows users to access the data through a web interface."
"The initial setup is straightforward."
"In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance."
"Amazon EMR's most valuable features are processing speed and data storage capacity."
"Amazon EMR is a good solution that can be used to manage big data."
"We use AWS Lake Formation typically for the data warehouse."
"The solution has many features that are applicable to events such as audits."
"The most important advantage in using AWS Lake Formation is its ability to connect the data lake to the other technologies in AWS. This is what I advise my clients."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."
"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."
"There is no need to pay extra for third-party software."
"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."
"Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana."
"The initial setup was time-consuming."
"The most complicated thing is configuring to the cluster and ensure it's running correctly."
"The product must add some of the latest technologies to provide more flexibility to the users."
"The solution could make improvements around orchestration and doing some automation stuff on AWS front automation. It would be useful if we could use automation to build images and use hardened images which are CIS compliant."
"It falls short when it comes to more granular access control, such as cell-level or row-level entitlements which is a significant drawback for organizations that require precise control over who can access specific rows of data."
"AWS Lake Formation's pricing could be cheaper."
"In our experience what could be improved are not the support, performance or monitoring, but at a managerial level, the very expensive professional services of AWS. This could be an area of improvement for them. It's too expensive to acquire their support."
"For the end-users, it's not as user-friendly as it could be."
Amazon EMR is ranked 9th in Cloud Data Warehouse with 20 reviews while AWS Lake Formation is ranked 12th in Cloud Data Warehouse with 5 reviews. Amazon EMR is rated 7.8, while AWS Lake Formation is rated 7.6. The top reviewer of Amazon EMR writes "Provides efficient data processing features and has good scalability ". On the other hand, the top reviewer of AWS Lake Formation writes "Strategically aligning data management in a multi-cloud environment with significant reporting challenges". Amazon EMR is most compared with Snowflake, Cloudera Distribution for Hadoop, Azure Data Factory, Amazon Redshift and SAP HANA, whereas AWS Lake Formation is most compared with Snowflake, Azure Data Factory, Amazon Redshift, Microsoft Azure Synapse Analytics and Apache Hadoop. See our AWS Lake Formation vs. Amazon EMR report.
See our list of best Cloud Data Warehouse vendors.
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.
