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Immutable database and Datalog query engine for Clojure, ClojureScript and JS

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A fast, immutable, distributed & compositional Datalog engine for everyone.

Quick Overview

Datascript is a Clojure/ClojureScript library that provides a powerful and flexible in-memory database solution. It allows developers to store and query data using a Datalog-inspired query language, making it a great choice for building applications that require efficient data management and querying capabilities.

Pros

  • Powerful Query Language: Datascript's Datalog-inspired query language provides a concise and expressive way to interact with data, making it easy to perform complex queries and data transformations.
  • Immutable Data Structure: Datascript uses an immutable data structure, which makes it easy to manage and reason about data changes, and supports efficient transactional updates.
  • ClojureScript Support: Datascript is available for both Clojure and ClojureScript, allowing developers to use it in both server-side and client-side applications.
  • Flexible and Extensible: Datascript is designed to be highly flexible and extensible, with support for custom data types and functions, making it suitable for a wide range of use cases.

Cons

  • Learning Curve: The Datalog-inspired query language used by Datascript may have a steeper learning curve for developers who are more familiar with traditional SQL-based databases.
  • Limited Persistence Options: Datascript is an in-memory database, which means that data is not persisted by default. Developers may need to integrate Datascript with a separate persistence layer, such as a file-based storage or a traditional database.
  • Performance Limitations: As an in-memory database, Datascript may have performance limitations for very large datasets or high-concurrency scenarios, where a traditional database might be more suitable.
  • Ecosystem Maturity: Compared to some other database solutions, the Datascript ecosystem may be less mature, with fewer third-party libraries and tools available.

Code Examples

Here are a few examples of how to use Datascript:

  1. Creating a Database and Inserting Data:
(require '[datascript.core :as d])

;; Create a new database
(def db (d/create-conn))

;; Insert some data
(d/transact! db [{:db/id 1 :name "Alice" :age 30}
                 {:db/id 2 :name "Bob" :age 25}
                 {:db/id 3 :name "Charlie" :age 35}])
  1. Querying the Database:
;; Query the database for people older than 30
(d/q '[:find ?e ?name ?age
      :where [?e :name ?name]
             [?e :age ?age]
             [(> ?age 30)]]
     @db)
  1. Updating Data:
;; Update Bob's age
(d/transact! db [{:db/id 2 :age 26}])
  1. Reverting Changes:
;; Revert the previous transaction
(d/transact! db [[:db/retract 2 :age 26]])

Getting Started

To get started with Datascript, you can add the following dependency to your project:

[datascript "1.2.9"]

Then, you can start using Datascript in your Clojure or ClojureScript code. Here's a simple example to get you started:

(require '[datascript.core :as d])

;; Create a new database
(def db (d/create-conn))

;; Insert some data
(d/transact! db [{:db/id 1 :name "Alice" :age 30}
                 {:db/id 2 :name "Bob" :age 25}
                 {:db/id 3 :name "Charlie" :age 35}])

;; Query the database
(d/q '[:find ?e ?name ?age
      :where [?e :name ?name]
             [?e :age ?age]
             [(> ?age 30)]]
     @db)

This example demonstrates how to create a new

Competitor Comparisons

A fast, immutable, distributed & compositional Datalog engine for everyone.

Pros of Datahike

  • Supports persistent storage and durability
  • Offers ACID transactions
  • Provides temporal querying capabilities

Cons of Datahike

  • Generally slower performance than Datascript
  • More complex setup and configuration
  • Smaller community and ecosystem

Code Comparison

Datascript:

(require '[datascript.core :as d])

(def conn (d/create-conn))
(d/transact! conn [{:db/id -1 :name "Alice" :age 30}])
(d/q '[:find ?n ?a :where [?e :name ?n] [?e :age ?a]] @conn)

Datahike:

(require '[datahike.api :as d])

(def cfg {:store {:backend :file :path "/tmp/example"}})
(d/create-database cfg)
(def conn (d/connect cfg))
(d/transact conn [{:db/id -1 :name "Alice" :age 30}])
(d/q '[:find ?n ?a :where [?e :name ?n] [?e :age ?a]] @conn)

Both Datascript and Datahike are Datalog-based databases for Clojure, but they have different focuses. Datascript is designed for in-memory usage and offers excellent performance for client-side applications. Datahike, on the other hand, provides persistence and ACID transactions, making it suitable for server-side applications that require data durability. The code comparison shows that while the basic usage is similar, Datahike requires additional configuration for storage backend.

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README

What if creating a database would be as cheap as creating a Hashmap?

An immutable in-memory database and Datalog query engine in Clojure and ClojureScript.

DataScript is meant to run inside the browser. It is cheap to create, quick to query and ephemeral. You create a database on page load, put some data in it, track changes, do queries and forget about it when the user closes the page.

DataScript databases are immutable and based on persistent data structures. In fact, they’re more like data structures than databases (think Hashmap). Unlike querying a real SQL DB, when you query DataScript, it all comes down to a Hashmap lookup. Or series of lookups. Or array iteration. There’s no particular overhead to it. You put a little data in it, it’s fast. You put in a lot of data, well, at least it has indexes. That should do better than you filtering an array by hand anyway. The thing is really lightweight.

The intention with DataScript is to be a basic building block in client-side applications that needs to track a lot of state during their lifetime. There’s a lot of benefits:

  • Central, uniform approach to manage all application state. Clients working with state become decoupled and independent: rendering, server sync, undo/redo do not interfere with each other.
  • Immutability simplifies things even in a single-threaded browser environment. Keep track of app state evolution, rewind to any point in time, always render consistent state, sync in background without locking anybody.
  • Datalog query engine to answer non-trivial questions about current app state.
  • Structured format to track data coming in and out of DB. Datalog queries can be run against it too.

Latest version Build Status

;; lein
[datascript "1.7.4"]
;; deps.edn
datascript/datascript {:mvn/version "1.7.4"}

Important! If you are using shadow-cljs, add

:compiler-options {:externs ["datascript/externs.js"]}

to your build (see #432 #298 #216)

Support us

Resources

Support:

Books:

Docs:

Posts:

Talks:

  • “Frontend with Joy” talk (FPConf, August 2015): video in Russian
  • “Programming Web UI with Database in a Browser” talk (PolyConf, July 2015): slides, video
  • “DataScript for Web Development” talk (Clojure eXchange, Dec 2014): slides, video
  • “Building ToDo list with DataScript” webinar (ClojureScript NYC, Dec 2014): video, app
  • DataScript hangout (May 2014, in Russian): video

Projects using DataScript:

Related projects:

  • DataScript-Transit, transit serialization for database and datoms
  • DataScript SQL Storages, durable storage implementations for popular SQL databases
  • Posh, lib that lets you use a single DataScript db to store Reagent app state
  • re-posh, use re-frame with DataScript storage
  • DataScript-mori, DataScript & Mori wrapper for use from JS
  • DatSync, Datomic ↔︎ DataScript syncing/replication utilities
  • Intension, lib to convert associative structures to in-memory databases for querying them
  • Datamaps, lib designed to leverage datalog queries to query arbitrary maps.

Demo applications:

Usage examples

For more examples, see our acceptance test suite.

(require '[datascript.core :as d])

;; Implicit join, multi-valued attribute

(let [schema {:aka {:db/cardinality :db.cardinality/many}}
      conn   (d/create-conn schema)]
  (d/transact! conn [ { :db/id -1
                        :name  "Maksim"
                        :age   45
                        :aka   ["Max Otto von Stierlitz", "Jack Ryan"] } ])
  (d/q '[ :find  ?n ?a
          :where [?e :aka "Max Otto von Stierlitz"]
                 [?e :name ?n]
                 [?e :age  ?a] ]
       @conn))

;; => #{ ["Maksim" 45] }


;; Destructuring, function call, predicate call, query over collection

(d/q '[ :find  ?k ?x
        :in    [[?k [?min ?max]] ...] ?range
        :where [(?range ?min ?max) [?x ...]]
               [(even? ?x)] ]
      { :a [1 7], :b [2 4] }
      range)

;; => #{ [:a 2] [:a 4] [:a 6] [:b 2] }


;; Recursive rule

(d/q '[ :find  ?u1 ?u2
        :in    $ %
        :where (follows ?u1 ?u2) ]
      [ [1 :follows 2]
        [2 :follows 3]
        [3 :follows 4] ]
     '[ [(follows ?e1 ?e2)
         [?e1 :follows ?e2]]
        [(follows ?e1 ?e2)
         [?e1 :follows ?t]
         (follows ?t ?e2)] ])

;; => #{ [1 2] [1 3] [1 4]
;;       [2 3] [2 4]
;;       [3 4] }


;; Aggregates

(d/q '[ :find ?color (max ?amount ?x) (min ?amount ?x)
        :in   [[?color ?x]] ?amount ]
     [[:red 10]  [:red 20] [:red 30] [:red 40] [:red 50]
      [:blue 7] [:blue 8]]
     3)

;; => [[:red  [30 40 50] [10 20 30]]
;;     [:blue [7 8] [7 8]]]

Using from vanilla JS

DataScript can be used from any JS engine without additional dependencies:

<script src="https://github.com/tonsky/datascript/releases/download/1.7.4/datascript-1.7.4.min.js"></script>

or as a CommonJS module (npm page):

npm install datascript
var ds = require('datascript');

or as a RequireJS module:

require(['datascript'], function(ds) { ... });

Queries:

  • Query and rules should be EDN passed as strings
  • Results of q are returned as regular JS arrays

Entities:

  • Entities returned by entity call are lazy as in Clojure
  • Use e.get("prop"), e.get(":db/id"), e.db to access entity properties
  • Entities implement ECMAScript 6 Map interface (has/get/keys/...)

Transactions:

  • Use strings such as ":db/id", ":db/add", etc. instead of db-namespaced keywords
  • Use regular JS arrays and objects to pass data to transact and db_with

Transaction reports:

  • report.tempids has string keys ("-1" for entity tempid -1), use resolve_tempid to set up a correspondence

Check out test/js/tests.js for usage examples.

Project status

Stable. Most of the features done, expecting non-breaking API additions and performance optimizations. No docs at the moment, use examples & Datomic documentation.

The following features are supported:

  • Database as a value: each DB is an immutable value. New DBs are created on top of old ones, but old ones stay perfectly valid too
  • Triple store model
  • EAVT, AEVT and AVET indexes
  • Multi-valued attributes via :db/cardinality :db.cardinality/many
  • Lazy entities and :db/valueType :db.type/ref auto-expansion
  • Database “mutations” via transact!
  • Callback-based analogue to txReportQueue via listen!
  • Direct index lookup and iteration via datoms and seek-datoms
  • Filtered databases via filter
  • Lookup refs
  • Unique constraints, upsert
  • Pull API (thx David Thomas Hume)

Query engine features:

  • Implicit joins
  • Query over DB or regular collections
  • Parameterized queries via :in clause
  • Tuple, collection, relation binding forms in :in clause
  • Query over multiple DB/collections
  • Predicates and user functions in query
  • Negation and disjunction
  • Rules, recursive rules
  • Aggregates
  • Find specifications

Interface differences:

  • Conn is just an atom storing last DB value, use @conn instead of (d/db conn)
  • Instead of #db/id[:db.part/user -100] just use -100 in place of :db/id or entity id
  • Transactor functions can be called as [:db.fn/call f args] where f is a function reference and will take db as first argument (thx @thegeez)
  • In ClojureScript, custom query functions and aggregates should be passed as source instead of being referenced by symbol (due to lack of resolve in CLJS)
  • Custom aggregate functions are called via aggregate keyword: :find (aggregate ?myfn ?e) :in $ ?myfn
  • Additional :db.fn/retractAttribute shortcut
  • Transactions are not annotated by default with :db/txInstant
  • When “transaction function” is called, the db that this function receive is a “partial db” relative to it's position in transaction.

Differences from Datomic

  • DataScript is built totally from scratch and is not related by any means to the popular Clojure database Datomic
  • Runs in a browser and/or in a JVM
  • Simplified schema, not queryable
  • Attributes do not have to be declared in advance. Put them to schema only when you need special behaviour from them
  • Any type can be used for values
  • No :db/ident for attributes, keywords are literally attribute values, no integer id behind them
  • No schema migrations
  • No full-text search, no partitions
  • No external dependencies

Aimed at interactive, long-living browser applications, DataScript DBs operate in constant space. If you do not add new entities, just update existing ones, or clean up database from time to time, memory consumption will be limited. This is unlike Datomic which keeps history of all changes, thus grows monotonically. DataScript does not track history by default, but you can do it via your own code if needed.

Some of the features are omitted intentionally. Different apps have different needs in storing/transfering/keeping track of DB state. DataScript is a foundation to build exactly the right storage solution for your needs without selling too much “vision”.

Contributing

Testing

Setup

npm install ws

Running the tests

clj -M:test -m kaocha.runner

Watching tests:

./script/watch.sh

Benchmarking and Datomic compatibility

datomic-free is a dependency not available on Clojars or Maven Central.

  1. Download datomic-free from https://my.datomic.com/downloads/free
  2. Unzip it
  3. Inside the unzipped folder run ./bin/maven-install

Run compatibility checks:

clj -M:datomic

Benchmark:

cd bench
./bench.clj

License

Copyright © 2014–2024 Nikita Prokopov

Licensed under Eclipse Public License (see LICENSE).

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