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- This is a subproject of [[http://www2.svjatoslav.eu/gitbrowse/sixth/doc/index.html][Sixth]]
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- Homepage: http://svjatoslav.eu
- Email: mailto://svjatoslav@svjatoslav.eu
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+* (document settings) :noexport:
+** use dark style for TWBS-HTML exporter
+#+HTML_HEAD: <link href="https://bootswatch.com/darkly/bootstrap.min.css" rel="stylesheet">
+#+HTML_HEAD: <script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/1.11.2/jquery.min.js"></script>
+#+HTML_HEAD: <script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.3.1/js/bootstrap.min.js"></script>"
+#+HTML_HEAD: <style type="text/css">
+#+HTML_HEAD: footer {background-color: #111 !important;}
+#+HTML_HEAD: pre {background-color: #111; color: #ccc;}
+#+HTML_HEAD: </style>
+
+* Vision / goal
+ :PROPERTIES:
+ :ID: f6764282-a6f6-44e6-8716-b428074dd093
+ :END:
+Provide versioned, clustered, flexible, distributed, multi-dimensional
+data storage engine for the [[http://www2.svjatoslav.eu/gitbrowse/sixth/doc/index.html][Sixth computation engine]].
+
++ Speaking of traditional relational database and object oriented
+ business applications:
+ + I hate object-relational impedance mismatch.
+
+ + I don't like to convert data between persistent database and
+ runtime objects for every transaction. How about creating united
+ database/computation engine instead to:
+ + Eliminate constant moving and converting of data between 2 systems.
+ + Abstract away difference between RAM VS persistent storage. Let
+ the system decide at runtime which data to keep in what kind of
+ memory.
+
+** Inspiration
++ Relational databases:
+ + Transactional.
+ + Indexable / Quickly searchable.
+
++ Git (version control system)
+ + Versionable
+ + Branchable / mergeable.
+ + Transparent cansistency, checksumming and deduplication.
+ + (Git as a database:
+ https://www.kenneth-truyers.net/2016/10/13/git-nosql-database/ )
+
++ Brain (appears to have more than 3D dimensional design. Food for
+ thought...)
+ + https://singularityhub.com/2017/06/21/is-there-a-multidimensional-mathematical-world-hidden-in-the-brains-computation/
+ + From there comes following idea: Maybe every problem can be
+ translated to geometry (use any shapes and as many dimensions as
+ you need). Solution(s) to such problems would then appear as
+ relatively simple search/comparison/lookup results. As a bonus,
+ such geometrical *data storage* AND *computation* can be
+ naturally made in *parallel* and *distributed*. That's what
+ neurons in the brain appear to be doing ! :) . Learning means
+ building/updating the model (the hard part). Question answering
+ is making (relatively simple) lookups (geometrical queries)
+ against the model.
+
* Current status
+- More or less defined [[id:f6764282-a6f6-44e6-8716-b428074dd093][Vision / goal]].
+
- Implemented very simple persistent key-value map.
+ - Long term goal is to use it as a backing storage engine and
+ implement more advanced features on top of this.
+
+* TODO
++ check out GRAKN.AI: database in the form of a knowledge graph that
+ uses machine reasoning to simplify data processing challenges for AI
+ applications.
+ + https://grakn.ai/
-Long term goal is to implement more advanced features on top of this.
++ check out Magma
+ + http://wiki.squeak.org/squeak/2665