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.
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.
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.
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.
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.
