grakn
typedb-bio
grakn | typedb-bio | |
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11 | 1 | |
3,671 | 73 | |
0.4% | - | |
9.3 | 4.6 | |
7 days ago | 10 months ago | |
Java | Python | |
Mozilla Public License 2.0 | - |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
grakn
- Datomic Is Now Free
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Best Websites For Coders
TypeDB : A Strongly-typed Database
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Fluree DB - A datomic like database that I just discovered
How does it compare to, say grakn (renamed https://vaticle.com/, I think?), or draph (https://dgraph.io/), or Ontotext's GraphDB (https://www.ontotext.com/products/graphdb/), or Datomic?
- Typedb
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Firebase is Dead: What is the Perfect Database in 2022?
Edge database looks pretty freakin awesome. It basically seems to re-write SQL and Graph databases together to create some new-ish programming language. It takes care of all the problems GraphQL has, and seems to be built separately but on top of postgres. It is really something unique, beautiful, and powerful. They don't have a security layer yet or a cloud hosting environment, but both are in the works. However, postgres still suffers from the scalable problems we all know. If you like unique fetching and strong typing, also check out TypeDB. It doesn't make its own list number because there is not cloud version, middleware, etc. However, worth checking out.
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Ask HN: Why are relational DBs are the standard instead of graph-based DBs?
If you find yourself limited by triplestores, there's also a new growing area of development in knowledge engines, which allow edges-of-edges, entailed relations, hypergraph relations, and more of the power you'd get from full logic programming. TypeDB (recently renamed from Grakn) is an example of that type of database.
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How Roche Discovered Novel Potential Gene Targets with TypeDB
In the story to follow, David presents how his team at Roche was able to identify potential novel targets that were not identified by Open Targets as highly ranked. This was made possible with TypeDB, which his team used to store the relevant data and then find underlying biological evidence for those new targets.
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Why are the downloaded zip files not in scope?
{ stdenv, lib, openjdk,typedbHome ? "~/.typedb_home", fetchzip}: let typedbVersion = "2.1.1"; typedbDirLinux = "typedb-all-linux-${typedbVersion}"; typedbDirMac = "typedb-all-mac-${typedbVersion}"; typedbDirWindows = "typedb-all-windows-${typedbVersion}"; typedbDir = if stdenv.hostPlatform.isWindows then typedbDirWindows else if stdenv.isDarwin then typedbDirMac else typedbDirLinux; linuxSrc = builtins.fetchTarball { url = "https://github.com/vaticle/typedb/releases/download/2.1.1/typedb-all-linux-2.1.1.tar.gz"; sha256 = "15nwm2dr68p67c2xcqigs66gd679j1zr72gqv7qxgvflwyvyz8fb"; }; windowsSrc = fetchzip { url = "https://github.com/vaticle/typedb/releases/download/2.1.1/typedb-all-windows-2.1.1.zip"; sha256 = "0vd66gfshkg697z07nhy957mwqzlli4r4pmn67hx58n9mkg024kq"; }; macSrc = fetchzip { url = "https://github.com/vaticle/typedb/releases/download/2.1.1/typedb-all-mac-2.1.1.zip"; sha256 = "16hlfy6kh2rnvcralz206q13mghb0rv8wazpg6q3h324p5rdys54"; }; srcFolder = if stdenv.hostPlatform.isWindows then windowsSrc else if stdenv.isDarwin then macSrc else linuxSrc ; javaPatch = '' 20c20 < JAVA_BIN=java --- > JAVA_BIN=${openjdk}/bin/java ''; in stdenv.mkDerivation rec { pname = "typedb"; version = typedbVersion; src = srcFolder; phases = [ "installPhase" ]; buildDepends = [ openjdk ]; installPhase = '' echo "here" # added for debugging ls -lah # " echo "--" # " #patch before install echo "${javaPatch}" > typedb_java.patch patch ./${typedbDir}/typedb typedb_java.patch mkdir $out cp -r ./${typedbDir} $out # add a wrapper script to $out that will move typedb to $typedb # this is necessary because typedb needs a writable environment echo " # on the first start copy everything to typedbHome if [ ! -f ${typedbHome}/typedb ]; then mkdir -p ${typedbHome}; cp -r $out/${typedbDir}/* ${typedbHome}; # correct permissions so that typedb and the user can write there chmod -R u+rw ${typedbHome} chmod u+x ${typedbHome}/typedb fi; ${typedbHome}/typedb \$@; " > $out/typedb chmod +x $out/typedb ''; doCheck = true; meta = with lib; { description = "TypeDB is a distributed knowledge graph: a logical database to organise large and complex networks of data as one body of knowledge."; longDescription = '' TypeDB is a distributed knowledge graph: a logical database to organise large and complex networks of data as one body of knowledge. TypeDB provides the knowledge engineering tools for developers to easily leverage the power of Knowledge Representation and Automated Reasoning when building complex systems. Ultimately, TypeDB serves as the knowledge-base foundation for intelligent systems. ''; homepage = "https://www.grakn.ai/"; license = licenses.gpl3Plus; platforms = platforms.all; maintainers = [ maintainers.haskie ]; }; }
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Best Websites Every Programmer Should Visit
grakn.ai : The Database for AI
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Need Graph Db Recommendations Lightweight Neo4j
Give the open-source Grakn a look as well (full transparency: I work there), it is an abstraction over a built in-house hypergraph storage engine and persisted layer using RocksDB. It's a logical database with a reasoning engine at the database level. https://github.com/graknlabs/grakn
typedb-bio
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How Roche Discovered Novel Potential Gene Targets with TypeDB
For this purpose, David built out a set of rules and schema in TypeQL. Below is just a very small excerpt of how such data can be modelled — taken from BioGrakn-Covid, a Vaticle community-led project by Konrad Mysliwiec (Data Science Software Engineer, Roche). Note that this is a selected schema; the full schema can be found within the BioGrakn-Covid schema file.
What are some alternatives?
datalevin - A simple, fast and versatile Datalog database
obsidian-garden - A knowledge management garden for https://obsidian.md, in which to grow your ideas
asami - A graph store for Clojure and ClojureScript
topic-db - TopicDB is a topic maps-based semantic graph store (using SQLite for persistence)
pygraft - Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
datahike - A durable Datalog implementation adaptable for distribution.
codex - CoDEx: A set of knowledge graph Completion Datasets Extracted from Wikidata and Wikipedia
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
ckb - Contextual knowledge bases
gremlin-scala - Scala wrapper for Apache TinkerPop 3 Graph DSL
scispacy - A full spaCy pipeline and models for scientific/biomedical documents.