--- title: Databases and Stores pagination_prev: demos/desktop/index pagination_next: demos/local/index --- import DocCardList from '@theme/DocCardList'; import {useCurrentSidebarCategory} from '@docusaurus/theme-common'; "Database" is a catch-all term referring to traditional RDBMS as well as K/V stores, document databases, and other "NoSQL" storages. There are many external database systems as well as browser APIs like WebSQL and `localStorage` ## Data Storage ### Structured Tables Database tables are a common import and export target for spreadsheets. One common representation of a database table is an array of JS objects whose keys are column headers and whose values are the underlying data values. For example, | Name | Index | | :----------- | ----: | | Barack Obama | 44 | | Donald Trump | 45 | | Joseph Biden | 46 | is naturally represented as an array of objects ```js [ { Name: "Barack Obama", Index: 44 }, { Name: "Donald Trump", Index: 45 }, { Name: "Joseph Biden", Index: 46 } ] ``` The `sheet_to_json` and `json_to_sheet` helper functions work with objects of similar shape, converting to and from worksheet objects. The corresponding worksheet would include a header row for the labels: ``` XXX| A | B | ---+--------------+-------+ 1 | Name | Index | 2 | Barack Obama | 44 | 3 | Donald Trump | 45 | 3 | Joseph Biden | 46 | ``` ### Unstructured Data "Schema-less" / "NoSQL" databases allow for arbitrary keys and values within the entries in the database. K/V stores and Objects add additional restrictions. There is no natural way to translate arbitrarily shaped schemas to worksheets in a workbook. One common trick is to dedicate one worksheet to holding named keys. For example, considering the JS object: ```json { "title": "SheetDB", "metadata": { "author": "SheetJS", "code": 7262 }, "data": [ { "Name": "Barack Obama", "Index": 44 }, { "Name": "Donald Trump", "Index": 45 }, ] } ``` A dedicated worksheet should store the one-off named values: ``` XXX| A | B | ---+-----------------+---------+ 1 | Path | Value | 2 | title | SheetDB | 3 | metadata.author | SheetJS | 4 | metadata.code | 7262 | ``` ## Data Interchange ### Exporting Data There are NodeJS connector libraries for many popular RDBMS systems. Libraries have facilities for connecting to a database, executing queries, and obtaining results as arrays of JS objects that can be passed to `json_to_sheet`. The main differences surround API shape and supported data types. For example, `better-sqlite3` is a connector library for SQLite. The result of a `SELECT` query is an array of objects suitable for `json_to_sheet`: ```js var aoo = db.prepare("SELECT * FROM 'Presidents' LIMIT 100000").all(); // highlight-next-line var worksheet = XLSX.utils.json_to_sheet(aoo); ``` Other databases will require post-processing. For example, MongoDB results include the Object ID (usually stored in the `_id` key). This can be removed before generating a worksheet: ```js const aoo = await db.collection('coll').find({}).toArray(); // highlight-next-line aoo.forEach((x) => delete x._id); const ws = XLSX.utils.json_to_sheet(aoo); ``` ### Importing Data When a strict schema is needed, the `sheet_to_json` helper function generates arrays of JS objects that can be scanned to determine the column "types". :::note Document databases like MongoDB tend not to require schemas. Arrays of objects can be used directly without setting up a schema: ```js const aoo = XLSX.utils.sheet_to_json(ws); // highlight-next-line await db.collection('coll').insertMany(aoo, { ordered: true }); ``` ::: The ["SQL Connectors"](/docs/demos/data/sql) demo includes sample functions for generating SQL CREATE TABLE and INSERT queries. ## DSV Interchange Many databases offer utilities for reading and writing CSV, pipe-separated documents, and other simple data files. They enable workflows where the library generates CSV data for the database to process or where the library parses CSV files created by the database. #### Worksheet to CSV CSV data can be generated from worksheets using `XLSX.utils.sheet_to_csv`. ```js // starting from a worksheet object const csv = XLSX.utils.sheet_to_json(ws); // whole workbook conversion const csv_arr = wb.SheetNames.map(n => XLSX.utils.sheet_to_json(wb.Sheets[n])); ``` #### CSV to Worksheet `XLSX.read` can read strings with CSV data. It will generate single-sheet workbooks with worksheet name `Sheet1`. Where supported, `XLSX.readFile` can read files. ```js // starting from a CSV string const ws_str = XLSX.read(csv_str, {type: "string"}).Sheets.Sheet1; // starting from a CSV binary string (e.g. `FileReader#readAsBinaryString`) const ws_bstr = XLSX.read(csv_bstr, {type: "binary"}).Sheets.Sheet1; // starting from a CSV file in NodeJS or Bun or Deno const ws_file = XLSX.readFile("test.csv").Sheets.Sheet1; ``` ## Demos ### Web APIs The following Web APIs are featured in separate demos: ### SQL Databases The following SQL-related topics are covered in separate demos: ### NoSQL Data Stores Demos for the following "NoSQL" data stores apply structured access patterns: Demos for the following "NoSQL" data stores apply unstructured access patterns: