HDFS vs Amazon S3
Developers should learn and use HDFS when building big data applications that require storing and processing petabytes of data, such as in data lakes, log analysis, or machine learning pipelines meets developers should learn amazon s3 when building cloud-native applications that require reliable, scalable, and secure storage for unstructured data such as images, videos, logs, or backups. Here's our take.
HDFS
Developers should learn and use HDFS when building big data applications that require storing and processing petabytes of data, such as in data lakes, log analysis, or machine learning pipelines
HDFS
Nice PickDevelopers should learn and use HDFS when building big data applications that require storing and processing petabytes of data, such as in data lakes, log analysis, or machine learning pipelines
Pros
- +It is particularly valuable in scenarios involving massive, sequential reads and writes, as it provides reliability through replication and scalability by adding more nodes to the cluster
- +Related to: apache-hadoop, apache-spark
Cons
- -Specific tradeoffs depend on your use case
Amazon S3
Developers should learn Amazon S3 when building cloud-native applications that require reliable, scalable, and secure storage for unstructured data such as images, videos, logs, or backups
Pros
- +It is essential for use cases like serving static assets for web applications, storing data for machine learning pipelines, or implementing disaster recovery solutions due to its high availability and integration with other AWS services
- +Related to: aws, cloud-storage
Cons
- -Specific tradeoffs depend on your use case
The Verdict
Use HDFS if: You want it is particularly valuable in scenarios involving massive, sequential reads and writes, as it provides reliability through replication and scalability by adding more nodes to the cluster and can live with specific tradeoffs depend on your use case.
Use Amazon S3 if: You prioritize it is essential for use cases like serving static assets for web applications, storing data for machine learning pipelines, or implementing disaster recovery solutions due to its high availability and integration with other aws services over what HDFS offers.
Developers should learn and use HDFS when building big data applications that require storing and processing petabytes of data, such as in data lakes, log analysis, or machine learning pipelines
Disagree with our pick? nice@nicepick.dev