Search Results for "hive"

Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data while making it possible for engines like Spark, Trino, Flink, Presto, Hive, and Impala to safely work with the same tables, at the same time. The core Java library that tracks table snapshots and metadata is complete, but still evolving. Current work is focused on adding row-level deletes and upserts, and integration work with new engines like Flink and Hive. The Iceberg format specification is being actively updated and is open for comment. ...

...The power of standard SQL and JDBC APIs with full ACID transaction capabilities and the flexibility of late-bound, schema-on-read capabilities from the NoSQL world by leveraging HBase as its backing store. Apache Phoenix is fully integrated with other Hadoop products such as Spark, Hive, Pig, Flume, and Map Reduce. Become the trusted data platform for OLTP and operational analytics for Hadoop through well-defined, industry-standard APIs. Apache Phoenix takes your SQL query, compiles it into a series of HBase scans, and orchestrates the running of those scans to produce regular JDBC result sets. Direct use of the HBase API, along with coprocessors and custom filters, results in performance on the order of milliseconds.

...Liquibase Core works with the following databases: Apache Derby, CockroachDB, Firebird, H2, HSQL, Informix, InterBase, MariaDB, MSSQL, MySQL, Oracle, PostgreSQL, SQLite, Sybase Anywhere, Sybase Enterprise. The databases that require extensions are: Azure Cosmos DB, Cassandra, Cache, DB2i, Hibernate, Impala/Hive, MaxDB, MongoDB, Redshift, SAP HANA, SQLFire, Snowflake, Teradata, Vertica, VoltDB. See Liquibase Database Tutorials. Liquibase can be integrated with Maven, Ant, Gradle, Spring Boot, and other CI/CD tools.

...Utilize the same file and data formats and metadata, security, and resource management frameworks as your Hadoop deployment, with no redundant infrastructure or data conversion/duplication. For Apache Hive users, Impala utilizes the same metadata and ODBC driver. Like Hive, Impala supports SQL, so you don't have to worry about reinventing the implementation wheel. With Impala, more users, whether using SQL queries or BI applications, can interact with more data through a single repository and metadata stored from source through analysis.

...This tool is developing high performance integrated data management platform which will seamlessly do Data Integration, Data Profiling, Data Quality, Data Preparation, Dummy Data Creation, Meta Data Discovery, Anomaly Discovery, Data Cleansing, Reporting and Analytic. It also had Hadoop ( Big data ) support to move files to/from Hadoop Grid, Create, Load and Profile Hive Tables. This project is also known as "Aggregate Profiler" Resful API for this project is getting built as (Beta Version) https://sourceforge.net/projects/restful-api-for-osdq/ apache spark based data quality is getting built at https://sourceforge.net/projects/apache-spark-osdq/

Original home : https://github.com/hangum/TadpoleForDBTools It is a tool to manage Altibase, Amazon RDS, Apache Hive,Apache Cassandra, Apache Tajo, MongoDB, CUBRID, MariaDB, MySQL, Oracle, MSSQL, SQLite, Tibero, PostgreSQL in Web Browser.