Apache Druid vs Apache Pinot
Apache Druid
druid.apache.org
Apache Pinot
pinot.apache.orgSide by side
| Figure | Apache Druid | Apache Pinot |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Big Data Analytics Software | 9.0 (#2) | 8.1 (#12) |
| Spec score · Stream Analytics Software | 9.0 (#2) | 8.2 (#6) |
| Spec score · Streaming Analytics Software | 9.0 (#2) | 8.1 (#4) |
| Spec score · OLAP Software | 9.0 (#3) | 8.2 (#11) |
| Spec score · Analytics Databases | 9.0 (#3) | 8.2 (#11) |
| Spec score · Analytics Data | 9.0 (#3) | 8.2 (#10) |
| Spec score · OLAP Databases | 9.0 (#3) | 8.1 (#10) |
| Spec score · Analytical Data Store Software | 9.0 (#4) | 8.2 (#9) |
| Spec score · Columnar Databases | 9.0 (#6) | 8.2 (#10) |
| Spec score · Database Software | 8.7 (#18) | 7.8 (#56) |
| Concurrency | The project describes Druid as supporting workloads from hundreds to tens of thousands of queries per second at consistent performance. | Pinot can serve hundreds of thousands of concurrent queries per second. |
| Deployment | Druid can run on commodity hardware in *NIX environments and is designed to run in AWS, GCP, Azure, and other cloud environments. | The official quick install supports Docker and Kubernetes with Helm. |
| Purpose | Apache Druid is a high-performance real-time analytics database for sub-second queries on streaming and batch data at scale. | Apache Pinot is a real-time distributed OLAP datastore for low-latency, high-throughput analytics and user-facing workloads. |
| Support | The project directs users to its community network for help using Druid. | The project provides Slack, mailing lists, GitHub Issues, and community meetups for questions and discussion. |
Plans
In their own words
Apache Druid
Apache Druid is a free, open-source analytics database for querying streaming and batch data. It is designed to return OLAP queries in milliseconds, including on high-cardinality datasets with billions to trillions of rows. The project describes applications ranging from hundreds to 100,000 queries per second. Native Apache Kafka and Amazon Kinesis integrations support low-latency ingestion and querying as data arrives. Druid organizes ingested data into columnar, time-indexed, encoded and compressed storage. Queries can use Druid SQL or JSON-over-HTTP, and joins are available during ingestion or at query time. Its web console can load data, manage datasources and tasks, show server status and run queries. Extensions connect to storage, databases and formats including S3, HDFS, Azure, PostgreSQL, Avro, ORC and Parquet. Druid can be self-hosted on Linux, macOS and other Unix-like systems; Windows is not supported. The local quickstart needs at least 6 GiB of RAM and Java 17. Production security controls require configuration.
Apache Pinot
Apache Pinot is a free, open-source distributed OLAP datastore for real-time analytics and user-facing workloads. It ingests streaming data from Apache Kafka, Apache Pulsar, and AWS Kinesis, plus batch data from Hadoop, Spark, Amazon S3, Azure ADLS, and Google Cloud Storage. Streaming and batch sources can be combined into one queryable table. Pinot provides SQL through a query editor and REST API, with JDBC, Java, Python, and Golang clients for applications. Project materials advertise P90 query latency in the tens of milliseconds on petabyte-scale data and capacity for hundreds of thousands of concurrent queries per second. Logical namespaces provide multitenancy. Security features include HTTP Basic Authentication, ACLs, TLS, mutual TLS, and row-level security filters in version 1.4.0 and later. Superset, Tableau, and Power BI can connect as BI tools. Official installation guidance covers Docker and Kubernetes with Helm. The self-hosted plan is listed at free.