Apache Druid
7.2#2 in streaming analytics softwareFree planFree planWebAPILinuxmacOS
VisitApache Druid vs Apache Storm
Apache Storm
6.6#8 in streaming analytics softwareFree planFree planWebAPILinuxmacOS
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| Fact | Apache Druid | Apache Storm |
|---|---|---|
| Deployment | Druid can run on commodity hardware in *NIX environments and is designed to run in AWS, GCP, Azure, and other cloud environments. | Storm provides local mode for in-process development and remote mode for submitting topologies to a cluster. |
| Integrations | Core extensions support systems and formats including S3, HDFS, Google Cloud Storage, Azure, Kafka, Kinesis, Avro, ORC, Parquet, MySQL, and PostgreSQL. | Out-of-the-box integrations include Apache Kafka, HDFS, JDBC databases, JMS, and Redis. |
| License | Apache Druid and its documentation are licensed under the Apache License, Version 2.0. | Apache Storm is licensed under the Apache License, Version 2.0. |
| Purpose | Apache Druid is a high-performance real-time analytics database for sub-second queries on streaming and batch data at scale. | Apache Storm is a distributed realtime computation system for reliably processing unbounded data streams. |
| Reliability | Druid provides continuous backup, automated recovery, and multi-node replication for high availability and durability. | Storm is designed to be scalable, fault-tolerant, and to guarantee data processing. |
| Security | Security features include TLS, authentication, and authorization, but they are disabled by default and the documentation says to configure them for production. | Storm supports pluggable Kerberos/SASL authentication and SimpleACLAuthorizer authorization, both disabled by default. |
| Support | The project directs users to its community network for help using Druid. | Users can get help through the user mailing list at [email protected]. |
Apache Druid plans
- Apache DruidFree
Apache Storm plans
- Apache StormFree
Pick Apache Druid if…
Druid suits teams building user-facing analytics or working with streaming data that need low-latency, concurrent queries and quick visibility into incoming data. It can also serve ad hoc analysis of semi-structured data such as JSON.
Pick Apache Storm if…
Storm suits developers building real-time stream-processing workloads such as analytics, ETL, or online machine learning. Its local and remote modes accommodate in-process development and cluster deployments.