What is Apache Hive?
Apache Hive is querying and analysis enabling software which runs on top of an Apache Hadoop instance. It provides the ability to perform SQL queries in distributed Hadoop storage, enabling reporting, analysis and functionality such as ETL, something which is natively not possible on a Hadoop Distributed File System. Using an interface similar to SQL called HiveQL, it enables the querying of data stored across large distributed databases and streamlines analysis of extremely large datasets.
Extract Data From Apache Hive
Loome makes it simple to connect to Apache Hive and extract data for downstream systems such as an Integration Hub, Reporting Data Store, Data Lake or Enterprise Data Warehouse. In-built features allow bulk selection of all source tables/files to be automatically synced on a regular schedule, minimising data load size leveraging incremental logic.
Natively Orchestrate Apache Hive Integration Tasks
Loome allows orchestration of data pipelines across data engineering, data science and high performance computing workloads with native integration of Apache Hive data pipeline tasks.
Loome provides a sophisticated workbench for configuration of job and task dependencies, scheduling, detailed logging, automated notifications and API access for dynamic task creation and execution.
Loome can execute tasks located as scripts in a GIT repository, entered via a web interface or by executing operations within a database. Loome includes support for native execution of SQL, Python, Spark, HIVE, PowerShell/PowerShell Core and Operating System commands.
Loome also simplifies control of deployment across multiple environments, and approval of changes between Development, Test and Production environments. Loome also allows you to scale your advanced pipelines to take advantage of on-demand clusters without changing a single line of code.