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Fluree has a Clojure client.

A note on terminology#

If you are familiar with Datomic, Datahike, Datascript, or Crux (or other Clojure triple-store+ databases) you may wonder at the difference in terminology between those databases and Fluree. Fluree uses RDF terminology to describe the relationships between entities, or subjects.

Here's a quick glossary of how your knowledge may map on to Fluree's terminology:

Clojure Triple-Store+ termFluree term


Make sure you have a running Fluree ledger service to connect to. See the Getting Started docs for more details.

Add to the artifact to your dependencies:

Leiningen -

[com.fluree/db "1.0.0-rc22"]

deps.edn -

com.fluree/db {:mvn/version "1.0.0-rc22"}

Require the api and establish a connection to your Fluree server:

(require '[fluree.db.api :as fdb])
(def conn (fdb/connect "http://localhost:8090"))
(def ledger "example/test")
@(fdb/new-ledger conn ledger)


transact is used to make any changes to the ledger, either adding data or schema. It's all data, and it all uses the same api to effect changes.


All data transacted into a ledger must conform to a schema. We'll transact a basic schema below. See the Schema documentation for more details.

Create a collection, which you can think of as a type of entity, or a relational database table.

;; creates book and author collections@(fdb/transact conn ledger [{:_id :_collection :_collection/name :book}                            {:_id :_collection :_collection/name :author}])
;; can also use strings like in the Fluree docs:;; {"_id" "_collection" "_collection/name" "author"}

Create some predicates for the collection, analogous to entity attributes or relational database columns.

@(fdb/transact conn ledger [{:_id :_predicate                             :_predicate/name :author/name                             :_predicate/doc "An author's complete name."                             :_predicate/unique true                             :_predicate/type :string                             :_predicate/upsert true}
                            {:_id :_predicate                             :_predicate/name :book/title                             :_predicate/doc "A book's title."                             :_predicate/unique true                             :_predicate/upsert true                             :_predicate/fullText true                             :_predicate/type :string}                            {:_id :_predicate                             :_predicate/name :book/notes                             :_predicate/doc "Any notes about the book"                             :_predicate/type :string}                            {:_id :_predicate                             :_predicate/name :book/authors                             :_predicate/doc "A book's authors."                             :_predicate/type :ref                             :_predicate/multi true                             :_predicate/restrictCollection :author}                            {:_id :_predicate                             :_predicate/name :book/tags                             :_predicate/doc "Tags for categorizing books."                             :_predicate/type :tag                             :_predicate/multi true}])


Insert some subject data that conforms to the schema we've created. See the Transact documentation for more details.

;; adding data@(fdb/transact conn ledger [{:_id :book                             :book/title "Watership Down"                             :book/tags [:rabbits :fiction]                             :book/authors [{:_id :author :name "Richard Adams"}]}                            {:_id :book                             :book/title "The Joy of Clojure"                             :book/tags [:programming :non-fiction]                             :book/authors [{:_id :author :name "Michael Fogus"}                                       {:_id :author :name "Chris Houser"}]}                            {:_id :book                             :book/title "Cryptonomicon"                             :book/tags [:fiction :sci-fi]                             :book/authors [{:_id :author :name "Neal Stephenson"}]}])
@(fdb/transact conn ledger [{:_id [:book/title "Cryptonomicon"]                             :book/notes "I rly liked it."}])
;; updating a single-cardinality predicate@(fdb/transact conn ledger [{:_id [:book/title "Cryptonomicon"]                             :book/notes "I really liked it."}])
;; updating a multi-cardinality predicate@(fdb/transact conn ledger [{:_id [:book/title "The Joy of Clojure"]                             :book/title "The Joy of Clojure"                             :book/tags [:favorite]}])  ; adding the :favorite tag
;; retracting a predicate@(fdb/transact conn ledger [{:_id [:book/title "Cryptonomicon"] :book/notes nil}])
;; retracting multi-cardinality member@(fdb/transact conn ledger [{:_id [:book/title "The Joy of Clojure"]                             :_action :delete                             :book/tags [:favorite]}]) ; only removing :favorite tag
;; retracting a whole subject@(fdb/transact conn ledger [{:_id [:book/title "Watership Down"] :_action :delete}])


Analytical queries#

The syntax for these queries is similar to datalog and eql. These don't support keywords for matching on flake values in the :where clause.

The query function takes a db value to execute a query against, as well as a query map. See the docs for Analytical queries and Basic queries for more details.

;; store the current immutable database value. See API docs for getting a prior version of a db, applying permissions to a db, and other options.(def db (fdb/db conn ledger))
;; all books@(fdb/query (fdb/db conn ledger) {:select {"?book" [:*, {:book/authors [:*]}]}                              :where [["?book" "book/title" nil]]})
;; all non-fiction books@(fdb/query (fdb/db conn ledger) {:select "?title"                              :where [["?book" "book/title" "?title"]                                      ["?book" "book/tags" "non-fiction"]]})

History queries#

History queries can show you the raw history of a subject. Use :pretty-print to get back maps of predicate names to object values instead of raw flake data.

;; see the history of the "Cryptonomicon" book.@(fdb/history-query (fdb/db conn ledger) {:history ["book/title" "Cryptonomicon"] :pretty-print true})

Block queries#

Block queries return all of the raw flake data stored in a block. Use :pretty-print to get back maps of predicate names to object values instead of raw flake data.

;; see all the flakes from block 3@(fdb/block_query-async conn ledger {:block 3 :pretty-print true})

Other query languages#

In addition to the FlureeQL syntax used above, Fluree also supports queries in other query languages: SQL, SPARQL, GraphQL. These can be used from Clojure by supplying a database value and a query string, or, in the case of GraphQL, a query map.

@(fdb/sql (fdb/db conn ledger) "select * from book")
@(fdb/sparql (fdb/db conn ledger) "SELECT ?title WHERE { ?book fd:book/title ?title; fd:book/tags \"sci-fi\".}")
@(fdb/graphql conn ledger {:query "{graph { book { _id title}}}"} )

Async API#

All of the interactions with the Fluree ledger server are performed asynchronously, returning a promise. If you prefer to work with core.async channels instead of promises, there are -async variants of all the functions mentioned here that will return a core.async channel which will receive the result when the operation has finished.

(require '[clojure.core.async :as async])
(async/<!! (fdb/query-async (fdb/db conn ledger) {:select ["*"] :from "book"}))