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Flink's Table API is a SQL-like expression language for relational stream and batch processing that can be embedded in Flink's Java and Scala DataSet and DataStream APIs. The Table API and SQL interface operate on a relational Table abstraction. Tables can be created from external data sources or from existing DataStreams and DataSets.
Query by Example (QBE) is a database query language for relational databases. It was devised by Moshé M. Zloof at IBM Research during the mid-1970s, in parallel to the development of SQL. [1] It is the first graphical query language, using visual tables where the user would enter commands, example elements and conditions.
SQL syntax can be checked at compile time. The returned query results can also be checked strictly. Preprocessor might generate static SQL which performs better than dynamic SQL because query plan is created on program compile time, stored in database and reused at runtime. Static SQL can guarantee access plan stability.
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.
The Jakarta Persistence Query Language (JPQL; formerly Java Persistence Query Language) is a platform-independent object-oriented query language [1]: 284, §12 defined as part of the Jakarta Persistence (JPA; formerly Java Persistence API) specification. JPQL is used to make queries against entities stored in a relational database.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
The nested set model is a technique for representing nested set collections (also known as trees or hierarchies) in relational databases.. It is based on Nested Intervals, that "are immune to hierarchy reorganization problem, and allow answering ancestor path hierarchical queries algorithmically — without accessing the stored hierarchy relation".
Type 3, the pure-java driver that talks with the server-side middleware that then talks to the database. Type 4, the pure-java driver that uses database native protocol. Note also a type called an internal JDBC driver - a driver embedded with JRE in Java-enabled SQL databases. It is used for Java stored procedures. This does not fit into the ...