Search Results for "document"

sq is a command line tool that provides jq-style access to structured data sources: SQL databases, or document formats like CSV or Excel. sq executes jq-like queries, or database-native SQL. It can join across sources: join a CSV file to a Postgres table, or MySQL with Excel. sq outputs to a multitude of formats including JSON, Excel, CSV, HTML, Markdown and XML, and can insert query results directly to a SQL database. sq can also inspect sources to view metadata about the source structure (tables, columns, size). ...

SJSON is a complement to GJSON, also written in Go, focused on setting or modifying values inside JSON documents through path expressions. Just as GJSON allows fast retrieval, SJSON allows fast mutation: you provide a JSON document, a dot-notation path (including array indices or the special “-1” index for appending), and a new value, and SJSON produces the updated JSON. It supports many data types (numbers, strings, bools, arrays, maps), raw byte paths, and options for in-place replacement. Because it avoids full unmarshalling into structs, it is very efficient for many use-cases where you just need to tweak a JSON document quickly. ...

CloverDB is a lightweight NoSQL database designed to be simple and easily maintainable, thanks to its small code base. It has been inspired by tinyDB. CloverDB has been written for being easily maintainable. As such, it trades performance with simplicity and is not intended to be an alternative to more performant databases such as MongoDB or MySQL. However, there are projects where running a separate database server may result overkilled, and, for simple queries, network delay may be the...

A simple Go package to Query over JSON Data. It provides a simple, elegant, and fast ODM-like API to access, and query JSON documents. You can query your document using the various query methods such as Find, First, Nth, Pluck, Where, OrWhere, WhereIn, WhereStartsWith, WhereEndsWith, WhereContains, Sort, GroupBy, SortBy, and so on. Also, you can aggregate data after query using Avg, Count, Max, Min, Sum, etc.