Installation

Datalevin can be installed with different methods, depending on how you plan to use it.

Clojure Library

The core of Datalevin is a JVM Clojure library, simply add it to your Clojure project as a dependency and start using it!

If you use Leiningen build tool, add this to the :dependencies section of your project.clj file:

[datalevin "0.9.22"]

If you use Clojure CLI and deps.edn, declare the dependency like so:

{:deps {datalevin/datalevin {:mvn/version "0.9.22"}}}

The master branch of this project is always kept fully functional, so if you need to use some yet-to-be released fixes or features, you can declare the dependency like so (remember to change :sha):

{:deps {:git/url "https://github.com/juji-io/datalevin.git"
        :sha "d839883e4dec35b89442fa8ebbd50c99a2b25a50"}}

This library supports Java 11 and above.

Performance Tip: To obtain better performance (about 5% to 20%), you may want to add the following JVM options to your project:

--add-opens=java.base/java.nio=ALL-UNNAMED
--add-opens=java.base/sun.nio.ch=ALL-UNNAMED

For lein, add a top level :jvm-opts in your project.clj like so:

:jvm-opts ["--add-opens=java.base/java.nio=ALL-UNNAMED"
           "--add-opens=java.base/sun.nio.ch=ALL-UNNAMED"]

For dep.edn, this is known to work:

:aliases {:jvm-base
           {:jvm-opts ["--add-opens=java.base/java.nio=ALL-UNNAMED"
                       "--add-opens=java.base/sun.nio.ch=ALL-UNNAMED"]}}

Then clj -A:jvm-base

Native Dependencies

For now, Datalevin requires some system libraries to be present, such as libc, libomp, and libmvec. These are easy to get:

• Linux needs OpenMP and Vectorized Math from GCC, e.g. on Debian/Ubuntu, apt-get install g++-12 gcc-12

• MacOSX needs the same libraries as the above from Clang, e.g. brew install libomp llvm

Otherwise, Datalevin may fail to load and report java.lang.UnsatisfiedLinkError.

Other JVM Languages

Datalevin can be used in other JVM languages than Clojure, such as Java, Scala, Kotlin, and so on, by using the official Clojure Java API. If you have done so, a PR to document your example will be welcome here. In addition, one can build a Datalevin wrapper in other JVM languages this way, and we will be happy to link to it here if you have done so.

Command Line Tool

A command line tool dtlv is built to work with Datalevin databases in shell scripting, doing work such as database backup/compaction, data import/export, query/transaction execution, server administration, and so on. The same binary can also run as a Datalevin server. This tool also includes a REPL with a Clojure interpreter, in addition to support all the database functions.

Unlike many other database software (e.g. SQLite, Postgres, etc.) that introduces a separate language for the command line, the same Clojure code works in both Datalevin library and Datalevin command line tool.

A native Datalevin is built by compiling into GraalVM native image.

These are the ways to get the Datalevin command line tool:

MacOS and Linux Package

Install using homebrew

brew install huahaiy/brew/datalevin

Windows Package

Install using scoop

# Note: if you get an error you might need to change the execution policy (i.e. enable Powershell) with
# Set-ExecutionPolicy RemoteSigned -scope CurrentUser
Invoke-Expression (New-Object System.Net.WebClient).DownloadString('https://get.scoop.sh')

scoop bucket add scoop-clojure https://github.com/littleli/scoop-clojure
scoop bucket add extras
scoop install datalevin

Docker

docker pull huahaiy/datalevin

See README on Docker hub for usage.

Direct Download

Or download the executable binary from github:

• Linux on x86_64 (AMD64)
• Linux on arm64 (AARCH64)
• MacOS on arm64 (AARCH64)
• MacOS on x86_64 (AMD64)
• Windows on x86-64 (AMD64)

Unzip to get a dtlv executable, put it on your path.

You may want to launch dtlv in rlwrap to get a better REPL experience.

Uberjar

A JVM uberjar is downloadable to use as the command line tool. It is useful when one wants to run a Datalevin server and needs the efficiency of JVM's JIT, as GraalVM native image is not as efficient as Hotspot JVM for long running programs, or when a pre-built native version is not available for your platform. For example:

java --add-opens=java.base/java.nio=ALL-UNNAMED --add-opens=java.base/sun.nio.ch=ALL-UNNAMED -jar datalevin-0.9.22-standalone.jar

This will start the Datalevin REPL.

java --add-opens=java.base/java.nio=ALL-UNNAMED --add-opens=java.base/sun.nio.ch=ALL-UNNAMED -jar datalevin-0.9.22-standalone.jar serv -r /tmp/test-server

Will run the Datalevin server on default port 8898, with root data path at /tmp/test-server.

Babashka Pod

The dtlv executable can also run as a Babashka pod. It is also possible to download Datalevin directly from pod registry within a Babashka script (not all versions are registered):

#!/usr/bin/env bb

(require '[babashka.pods :as pods])
(pods/load-pod 'huahaiy/datalevin "0.9.22")

For pod usage, an extra macro defpodfn is provided to define a custom function that can be used in a query, e.g.:

$ rlwrap bb
Babashka v1.3.181 REPL.
Use :repl/quit or :repl/exit to quit the REPL.
Clojure rocks, Bash reaches.

user=> (require '[babashka.pods :as pods])
nil
user=> (pods/load-pod "dtlv")
#:pod{:id "pod.huahaiy.datalevin"}
user=> (require '[pod.huahaiy.datalevin :as d])
nil
user=> (d/defpodfn custom-fn [n] (str "hello " n))
#:pod.huahaiy.datalevin{:inter-fn custom-fn}
user=> (d/q '[:find ?greeting :where [(custom-fn "world") ?greeting]])
#{["hello world"]}
user=> (def conn (d/get-conn "/tmp/bb-test"))
#'user/conn
user=> (d/transact! conn [{:name "hello"}])
{:datoms-transacted 1}
user=> (d/q '[:find ?n :where [_ :name ?n]] (d/db conn))
#{["hello"]}
user=> (d/close conn)
nil
user=>

The example above uses dtlv binary in the PATH.