We performed a comparison between Apache Hadoop 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 scalability of Apache Hadoop is very good."
"Most valuable features are HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect."
"The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."
"The performance is pretty good."
"It's open-source, so it's very cost-effective."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."
"Hadoop File System is compatible with almost all the query engines."
"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."
"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"The solution has many features that are applicable to events such as audits."
"We use AWS Lake Formation typically for the data warehouse."
"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts of data."
"From the Apache perspective or the open-source community, they need to add more capabilities to make life easier from a configuration and deployment perspective."
"It requires a great deal of learning curve to understand. The overall Hadoop ecosystem has a large number of sub-products. There is ZooKeeper, and there are a whole lot of other things that are connected. In many cases, their functionalities are overlapping, and for a newcomer or our clients, it is very difficult to decide which of them to buy and which of them they don't really need. They require a consulting organization for it, which is good for organizations such as ours because that's what we do, but it is not easy for the end customers to gain so much knowledge and optimally use it."
"The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support."
"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."
"The stability of the solution needs improvement."
"I would like to see more direct integration of visualization applications."
"What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly."
"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."
"For the end-users, it's not as user-friendly as it could be."
"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."
"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."
Apache Hadoop is ranked 5th in Data Warehouse with 31 reviews while AWS Lake Formation is ranked 12th in Cloud Data Warehouse with 5 reviews. Apache Hadoop is rated 7.8, while AWS Lake Formation is rated 7.6. The top reviewer of Apache Hadoop writes "A file system for data collection that contains needed information and files". 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". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Azure Data Factory, Oracle Exadata, Snowflake and SAP IQ, whereas AWS Lake Formation is most compared with Snowflake, Azure Data Factory, Amazon Redshift and Microsoft Azure Synapse Analytics. See our AWS Lake Formation vs. Apache Hadoop 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.