Apache Druid vs Apache Hive
Apache Druid
druid.apache.org
Apache Hive
hive.apache.orgSide by side
| Figure | Apache Druid | Apache Hive |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Big Data Analytics Software | 9.0 (#2) | 8.9 (#4) |
| Spec score · Analytics Databases | 9.0 (#3) | 9.0 (#4) |
| Spec score · OLAP Databases | 9.0 (#3) | 8.9 (#5) |
| 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 quickstart provides Docker instructions for running HiveServer2 and the Metastore in a container. |
| Integrations | Core extensions support systems and formats including S3, HDFS, Google Cloud Storage, Azure, Kafka, Kinesis, Avro, ORC, Parquet, MySQL, and PostgreSQL. | The project site names Spark, Presto, and Impala as integrations; it also describes Apache Ranger for authorization and Apache Atlas for lineage and governance. |
| Purpose | Apache Druid is a high-performance real-time analytics database for sub-second queries on streaming and batch data at scale. | Apache Hive is a distributed, fault-tolerant data warehouse system for reading, writing, and managing large datasets with SQL. |
| Security | Security features include TLS, authentication, and authorization, but they are disabled by default and the documentation says to configure them for production. | The site describes Kerberos authentication, fine-grained access control, and audit logging; HiveServer2 documentation also lists LDAP, PAM, and custom authentication options. |
| What it does | Apache Druid is a real-time analytics database for sub-second queries on streaming and batch data at scale. | Apache Hive is distributed data-warehouse software for reading, writing and managing very large datasets in distributed storage through SQL. |
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 Hive
Apache Hive is a distributed data warehouse system for reading, writing, and managing large datasets with SQL. Its Metastore keeps shared metadata for tables and partitions and serves clients including Hive, Impala, and Spark; HiveServer2 supports concurrent clients through JDBC and ODBC. Hive provides full ACID transactions for ORC tables and insert-only transactions for other formats. Documented storage options include S3, Azure Data Lake, and Google Cloud Storage, and Hive supports Apache Iceberg tables through a StorageHandler. Named integrations include Spark, Presto, and Impala, with Apache Ranger for authorization and Apache Atlas for lineage and governance. Security options described by the project include Kerberos, fine-grained access control, and audit logging; HiveServer2 also lists LDAP, PAM, and custom authentication. The quickstart includes Docker instructions for the server and Metastore. Hive is free open-source software. The installation manual lists Java 8, Maven 3.6.3, Protobuf 2.5, Hadoop 3.3.6, and Tez among current prerequisites; Hive 4.2.x instead requires JDK 21 minimum and works with Hadoop 3.4.1 and Tez 0.10.5.