A lightweight database based on
datascript and a
pluggable storage for data durability. In fact, mamulengo
has probably poor performance when compared to other
solutions and its purpose is small-sized applications that
need an embedded database to get its business moving.
If you are also interesting to learn more about its internals, it has a very simple architecture and can be really useful to study purpose.
We use datascript as the main database, but write every transaction to a durable storage. Therefore, because of this simple addition we are able to provide i) durability and ii) time-travel feature as in Datomic.
Datomic doesn't fit for small projects so well, therefore many projects who could benefit from it, can't. This library aims to provide a feel for Datalog/Datomic to newcomers.
Mamulengo supports PostgreSQL and H2 for Clojure and Local Storage for ClojureScript as durable storages.
This project follows the version scheme MAJOR.MINOR.COMMITS where MAJOR and MINOR provide some relative indication of the size of the change, but do not follow semantic versioning. In general, all changes endeavor to be non-breaking (by moving to new names rather than by breaking existing names). COMMITS is an ever-increasing counter of commits since the beginning of this repository.
Leinigen/Boot
[mamulengo "1.0.72"]
Clojure CLI/deps.edn
mamulengo {:mvn/version "1.0.72"}
(require '[mamulengo.core :as m])
(def cfg {:durable-storage :postgresql
:durable-conf {:dbtype "postgresql"
:dbname "mamulengo"
:password "test"
:user "test"}})
;;; let's define a schema
(def schema-planets
{:body/name {:db/cardinality :db.cardinality/one
:db/unique :db.unique/identity}
:body/diameter {:db/cardinality :db.cardinality/one
:db/unique :db.unique/identity}})
(m/connect! cfg schema-planets)
;;; now you are ready to save your data!!
(m/transact! [{:db/id -1
:body/name "Earth"
:body/diameter 12740}
{:db/id -2
:body/name "Pluto"
:body/diameter 80}
{:db/id -3
:body/name "Venus"
:body/diameter 12100}])
;;; you should also retrieve it back!
(m/query! '[:find (pull ?e [*])
:in $ ?n
:where
[?e :body/name ?n]]
"Pluto")
All the current durable storages has support for time-travel. The API behaves similarly with Datomic one, you can pass an old Database/Connection object to the query function.
(def db-as-of (m/as-of! #inst "2020-02-18T11:46:31.505-00:00"))
;;; more things happening...
(m/query! '[:find ?name
:where [?e :body/name ?name]]
db-as-of)
;;; more things...
(def db-since (m/since! #inst "2020-02-18T11:46:31.505-00:00"))
;;; you can also use the history database to query data across all time.
(def db-history (m/history!))
You can only capture a database using a timestamp, an option to use the transaction id might be on the way.
Please, see either time-travel-{pg,h2}-test
namespaces to
see some working examples.
mamulengo
?I just discover the project called datahike which is a lot more sophisticated and complete than mamulengo.
Apart from the hitchhiker-tree algorithm used in the project, both of them has very similar goals and ways to extend for different durable storages.
mamulengo
has the apparent advantage of easier
architecture to understand how the whole system works if you
are interested in its internals. However, mamulengo
has no
intention to become more robust to handle large
applications, it will remain as an alternative to newcomers
to use in their small personal projects and to learn
datalog.
Feel free to try both!!
mamulengo
?In Brazilian culture we have a very famous event in the northeast region called mamulengo which is a puppet theater. In front of the public we have the puppets that entertain and captivate the audience and behind it we have the hands of the artist that brings movements and voice to the puppets.
Mamulengo
here has the same objectives, we want you to be
amazed by datalog
query engines and all the bells and
whistle of immutable databases, but behind the scenes we manage the hard work to make this possible with no overhead
introduced to the audience.
The idea came from Rodolfo Ferreira about rethinking some concepts on databases and reaching the conclusion that not all applications need an insane amount of write/reads per second. Sometimes we only need a SQLite to do our work and go home happily.
However, we still want the advantages of Datascript and Immutable data sources.
The very initial code was inspired in https://gitlab.com/kurtosys/lib/factoidic.
Copyright © 2020 Wanderson Ferreira
This program and the accompanying materials are made available under the terms of the Eclipse Public License 2.0 which is available at http://www.eclipse.org/legal/epl-2.0.
This Source Code may also be made available under the following Secondary Licenses when the conditions for such availability set forth in the Eclipse Public License, v. 2.0 are satisfied: GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version, with the GNU Classpath Exception which is available at https://www.gnu.org/software/classpath/license.html.
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