Hive ODBC & JDBC Data Connectors with SQL Connector
Direct and universal data access for Apache Hive that simply works
Magnitude Simba Apache Hive connectors efficiently transform an application’s SQL query into the equivalent form in HiveQL. The Hive Query Language, a subset of SQL-92, allows Simba’s solutions to interrogate Hive to obtain schema information to present to a SQL-based application. Queries, including joins, are translated from SQL to HiveQL. Market leaders such as Alteryx®, DataStax®, Hortonworks®, MapR® are powered by Simba standards-based ODBC and JDBC to enable Business Intelligence (BI), analytics, and reporting on Hive-based data.
Hive is a data warehouse system for Hadoop that facilitates easy data summarization, ad-hoc queries, and the analysis of large datasets stored in Hadoop compatible file systems.
Simba’s ODBC and JDBC standardized solutions enable standard SQL-92
access directly to Apache Hive distributions. They efficiently map SQL
to HiveQL delivering full SQL application functionality and real-time
analytic and reporting capabilities to users.
- Direct BI connectivity to data without extraction
- Only direct, universal ODBC 3.8 data access solution for Apache Hive
- Powerful SQL Connector allows users to define schemas on the fly on schema-less data
- Full compatibility with leading analytic/reporting apps, including Alteryx, Microsoft Excel, Tableau, PowerBI and more
- Complies with latest ODBC 3.8 specification
- Complies with latest JDBC 4.1 and 4.2 specification
- Maps SQL to HiveQL
- HiveQL pass-through query option
- Provides full connector and query metadata
- Works with HiveServer2
- Supports all major on-premise and cloud Hadoop / Hive distributions: Apache, Cloudera, DataStax, Hortonworks, MapR and others
- Supports Apache Hive versions 0.11 through 3.1
- Supports 32- and 64-bit applications
- Supports Unicode
- Supports multiple platforms, including Windows, RedHat, SUSE, Solaris SPARC, AIX, and Mac OS X
- Supports HiveQL: SELECT, INSERT [OVERWRITE] SELECT, LOAD, and CREATE/DROP statements
- Supports ANSI SQL-92: SELECT/ORDER BY/GROUP BY/HAVING/CROSSJOIN/INNER JOIN/(LEFT|RIGHT|FULL) OUTER JOIN|UNION ALL
- Supports data types: TinyInt, SmallInt, Int, BigInt, Float, Double, Boolean, String, Decimal and TimeStamp
User Guides, Release Notes, and FAQs.