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  2. Apache Hive - Wikipedia

    en.wikipedia.org/wiki/Apache_Hive

    Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.

  3. Apache Hadoop - Wikipedia

    en.wikipedia.org/wiki/Apache_Hadoop

    HDFS: Hadoop's own rack-aware file system. [47] This is designed to scale to tens of petabytes of storage and runs on top of the file systems of the underlying operating systems. Apache Hadoop Ozone: HDFS-compatible object store targeting optimized for billions of small files. FTP file system: This stores all its data on remotely accessible FTP ...

  4. Data warehouse - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse

    Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...

  5. Presto (SQL query engine) - Wikipedia

    en.wikipedia.org/wiki/Presto_(SQL_query_engine)

    Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, [1] and allows use of multiple data sources within a query.

  6. Shard (database architecture) - Wikipedia

    en.wikipedia.org/wiki/Shard_(database_architecture)

    A database shard, or simply a shard, is a horizontal partition of data in a database or search engine. Each shard may be held on a separate database server instance, to spread load. Some data in a database remains present in all shards, [a] but some appears only in a single shard. Each shard acts as the single source for this subset of data. [1]

  7. SAP IQ - Wikipedia

    en.wikipedia.org/wiki/SAP_IQ

    SAP IQ provides federation with the Hadoop distributed file system (HDFS), a very popular framework for big data, so that enterprise users can continue to store data in Hadoop and utilize its benefits. Integration is achieved in four different ways, depending on the user's needs, through client-side federation, ETL, data, and query federation.

  8. Apache Impala - Wikipedia

    en.wikipedia.org/wiki/Apache_Impala

    Impala is integrated with Hadoop to use the same file and data formats, metadata, security and resource management frameworks used by MapReduce, Apache Hive, Apache Pig and other Hadoop software. Impala is promoted for analysts and data scientists to perform analytics on data stored in Hadoop via SQL or business intelligence tools. The result ...

  9. Data-intensive computing - Wikipedia

    en.wikipedia.org/wiki/Data-intensive_computing

    These include HBase, a distributed column-oriented database which provides random access read/write capabilities; Hive, which is a data warehouse system built on top of Hadoop that provides SQL-like query capabilities for data summarization, ad hoc queries, and analysis of large datasets; and Pig – a high-level data-flow programming language ...