# Datomish Datomish is a persistent, embedded knowledge base. It's written in ClojureScript, and draws heavily on [DataScript](https://github.com/tonsky/datascript) and [Datomic](http://datomic.com). Datomish compiles into a single JavaScript file, and is usable both in Node (on top of `promise_sqlite`) and in Firefox (on top of `Sqlite.jsm`). It also works in pure Clojure on the JVM on top of `jdbc-sqlite`. There's an example Firefox restartless add-on in the [`addon`](https://github.com/mozilla/datomish/tree/master/addon) directory; build instructions are below. We are in the early stages of reimplementing Datomish in [Rust](https://www.rust-lang.org/). You can follow that work in [its long-lived branch](https://github.com/mozilla/datomish/tree/rust), and issue #133. ## Motivation Datomish is intended to be a flexible relational (not key-value, not document-oriented) store that doesn't leak its storage schema to users, and doesn't make it hard to grow its domain schema and run arbitrary queries. Our short-term goal is to build a system that, as the basis for a User Agent Service, can support multiple [Tofino](https://github.com/mozilla/tofino) UX experiments without having a storage engineer do significant data migration, schema work, or revving of special-purpose endpoints. By abstracting away the storage schema, and by exposing change listeners outside the database (not via triggers), we hope to allow both the data store itself and embedding applications to use better architectures, meeting performance goals in a way that allows future evolution. ## Comparison to DataScript DataScript asks the question: "What if creating a database would be as cheap as creating a Hashmap?" Datomish is not interested in that. Instead, it's strongly interested in persistence and performance, with very little interest in immutable databases/databases as values or throwaway use. One might say that Datomish's question is: "What if an SQLite database could store arbitrary relations, for arbitrary consumers, without them having to coordinate an up-front storage-level schema?" (Note that [domain-level schemas are very valuable](http://martinfowler.com/articles/schemaless/).) Another possible question would be: "What if we could bake some of the concepts of CQRS and event sourcing into a persistent relational store, such that the transaction log itself were of value to queries?" Some thought has been given to how databases as values — long-term references to a snapshot of the store at an instant in time — could work in this model. It's not impossible; it simply has different performance characteristics. Just like DataScript, Datomish speaks Datalog for querying and takes additions and retractions as input to a transaction. Unlike DataScript, Datomish's API is asynchronous. Unlike DataScript, Datomish exposes free-text indexing, thanks to SQLite. ## Comparison to Datomic Datomic is a server-side, enterprise-grade data storage system. Datomic has a beautiful conceptual model. It's intended to be backed by a storage cluster, in which it keeps index chunks forever. Index chunks are replicated to peers, allowing it to run queries at the edges. Writes are serialized through a transactor. Many of these design decisions are inapplicable to deployed desktop software; indeed, the use of multiple JVM processes makes Datomic's use in a small desktop app, or a mobile device, prohibitive. Datomish is designed for embedding, initially in an Electron app ([Tofino](https://github.com/mozilla/tofino)). It is less concerned with exposing consistent database states outside transaction boundaries, because that's less important here, and dropping some of these requirements allows us to leverage SQLite itself. ## Comparison to SQLite SQLite is a traditional SQL database in most respects: schemas conflate semantic, structural, and datatype concerns; the main interface with the database is human-first textual queries; sparse and graph-structured data are 'unnatural', if not always inefficient; experimenting with and evolving data models are error-prone and complicated activities; and so on. Datomish aims to offer many of the advantages of SQLite — single-file use, embeddability, and good performance — while building a more relaxed and expressive data model on top. ## Contributing Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. See [CONTRIBUTING.md](/CONTRIBUTING.md) for further notes. This project is very new, so we'll probably revise these guidelines. Please comment on an issue before putting significant effort in if you'd like to contribute. ## License Datomish is currently licensed under the Apache License v2.0. See the `LICENSE` file for details. Datomish includes some code from DataScript, kindly relicensed by Nikita Prokopov. ## SQLite dependencies Datomish uses partial indices, which are available in SQLite 3.8.0 and higher. It also uses FTS4, which is [a compile time option](http://www.sqlite.org/fts3.html#section_2). ## Prep You'll need [Leiningen](http://leiningen.org). ``` # If you use nvm. nvm use 6 lein deps npm install # If you want a decent REPL. brew install rlwrap ``` ## Running a REPL ### Starting a ClojureScript REPL from the terminal ``` rlwrap lein run -m clojure.main repl.clj ``` ### Connecting to a ClojureScript environment from Vim You'll need `vim-fireplace`. Install using Pathogen. First, start a Clojure REPL with an nREPL server. Then load our ClojureScript REPL and dependencies. Finally, connect to it from Vim. ``` $ lein repl nREPL server started on port 62385 on host 127.0.0.1 - nrepl://127.0.0.1:62385 REPL-y 0.3.7, nREPL 0.2.10 Clojure 1.8.0 Java HotSpot(TM) 64-Bit Server VM 1.8.0_60-b27 Docs: (doc function-name-here) (find-doc "part-of-name-here") Source: (source function-name-here) Javadoc: (javadoc java-object-or-class-here) Exit: Control+D or (exit) or (quit) Results: Stored in vars *1, *2, *3, an exception in *e user=> (load-file "repl.clj") Reading analysis cache for jar:file:/Users/rnewman/.m2/repository/org/clojure/clojurescript/1.9.89/clojurescript-1.9.89.jar!/cljs/core.cljs Compiling out/cljs/nodejs.cljs Compiling src/datomish/sqlite.cljs Compiling src/datomish/core.cljs ClojureScript Node.js REPL server listening on 57134 Watch compilation log available at: out/watch.log To quit, type: :cljs/quit cljs.user=> ``` in Vim, in the working directory: ``` :Piggieback (cljs.repl.node/repl-env) ``` Now you can use `:Eval`, `cqc`, and friends to evaluate code. Fireplace should connect automatically, but if it doesn't: ``` :Connect nrepl://localhost:62385 ``` ## To run tests in ClojureScript Run `lein doo node test once`, or `lein doo node test auto` to re-run on file changes. ## To run tests in Clojure Run `lein test`. ## To run smoketests with the built release library in a Node environment ``` # Build. lein cljsbuild once release-node npm run test ``` ## To build for a Firefox add-on ``` lein cljsbuild once release-browser ``` ### To build and run the example Firefox add-on: First build as above, so that `datomish.js` exists. Then: ``` cd addon ./build.sh cd release ./run.sh ``` ## Preparing an NPM release The intention is that the `target/release-node/` directory is roughly the shape of an npm-ready JavaScript package. To generate a require/import-ready `target/release-node/datomish.js`, run ``` lein cljsbuild once release-node ``` To verify that importing into Node.js succeeds, run ``` npm run test ``` ## To locally install for ClojureScript use ``` lein with-profile node install ``` Many thanks to ([David Nolen](https://github.com/swannodette)) and ([Nikita Prokopov](https://github.com/tonsky)) for demonstrating how to package ClojureScript for distribution via npm.