Apache Beam vs Apache Hive
Apache Beam
beam.apache.org
Apache Hive
hive.apache.orgSide by side
| Figure | Apache Beam | Apache Hive |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | Yes |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · Big Data Analytics Software | 9.1 (#1) | 8.9 (#4) |
| Extensibility | TensorFlow Extended and Apache Hop are examples of projects built on Beam. | Hive SQL supports user-defined functions for custom analysis. |
| Security | Apache release files include OpenPGP signatures and SHA-512 checksums so users can verify downloaded files. | The site describes Kerberos authentication, fine-grained access control, and audit logging; HiveServer2 documentation also lists LDAP, PAM, and custom authentication options. |
| Self-hosting | Direct, Flink, Spark, Samza, Twister2 and other runners allow pipelines to run on user-managed infrastructure, while Dataflow is managed. | Users can install Hive from a binary tarball or clone the Git repository and build a distribution with Maven. |
| What it does | Apache Beam is an open-source programming model for building batch and streaming data-processing pipelines. | 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 Beam
Apache Beam is an open-source programming model for building data-processing pipelines across batch and streaming workloads. The same model can support both patterns in production, while runners provide different execution back ends, including Dataflow, Flink, Spark, and the Direct Runner. SDKs and quickstarts cover Java, Python, Go, and TypeScript. Pipeline building blocks include ParDo, GroupByKey, Flatten, and Combine, alongside windowing and triggering. Beam I/O connectors supply read and write transforms for external storage in batch or streaming pipelines, with catalog examples such as BigQuery, Snowflake, Apache Parquet, and Apache Iceberg. Beam Playground provides a way to try examples and transforms without a local installation. The software is free and open source; the listed plan is free, but execution costs depend on the runner and infrastructure selected. It targets data and software developers building pipelines on supported back ends. APIs may change before the first stable 1.x release, and semantic-versioning practice has exceptions.
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.