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GitHub uses Tree-sitter to support in-browser symbolic code navigation in Git repositories. [13] Tree-sitter uses a GLR parser, a type of LR parser. [14] [15] [13] Tree-sitter was originally developed by GitHub for use in the Atom text editor, where it was first released in 2018. [16] [6]
jq by default acts as a "stream editor" for JSON inputs, much like the sed utility can be thought of as a "stream editor" for lines of text. However jq has several other modes of operation: it can treat its input from one or more sources as lines of text; it can gather a stream of inputs from a specified source into a JSON array;
Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain a variety of file formats such as simple row-oriented CSV and JSON data files to more performant open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like ...
Amazon Ion – a superset of JSON (though limited to UTF-8, like JSON for interchange, unlike general JSON) Jackson (API) jaql – a functional data processing and query language most commonly used for JSON query processing; jq – a "JSON query language" and high-level programming language
RethinkDB is a free and open-source, distributed document-oriented database originally created by the company of the same name. The database stores JSON documents with dynamic schemas, and is designed to facilitate pushing real-time updates for query results to applications.
It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. Official clients are available in Java, [2].NET [3] , PHP, [4] Python, [5] Ruby [6] and many other languages. [7] According to the DB-Engines ranking, Elasticsearch is the most popular enterprise search engine. [8]
DuckDB is an open-source column-oriented relational database management system (RDBMS). [1] It is designed to provide high performance on complex queries against large databases in embedded configuration, [2] such as combining tables with hundreds of columns and billions of rows.
Dynamic indexes - in RavenDB is that queries can only be satisfied by an index; if no appropriate index exists, a new index is created to satisfy the query. [ 6 ] [ 16 ] [ 4 ] [ 23 ] [ 24 ] [ 10 ] Graph querying - related documents can be treated as vertices in a graph, with the connections treated as edges.