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cwbe coordinatez:
101
63540
63542
8188908

ABSOLUT
KYBERIA
permissions
you: r,
system: public
net: yes

neurons

stats|by_visit|by_K
source
tiamat
K|my_K|given_K
last
commanders
polls

total descendants::15
total children::12
5 K

show[ 2 | 3] flat


ianus0
s70
Jay0
ulkas0
ventYl0
oolerin0
vygidor11
drakh13
https://neo4j.com/

najpouzivanejsia grafova databaza sucasnosti.
zakladnym principom grafovych databaz je rozbitie dat na zakladne jednotky. oproti SQL databaze to znamena vylucenie tabuliek ako takych, a len drzanie samostatnych riadkov a ich buniek ako datovych jednotiek v jednej velkej akokeby tabulke.

pri dotazoch sa potom nedohladava konkretna tabulka, ale vzdy len startovaci bod, od ktoreho chcem dostat relevantne data. v zmysle ryzhlosti to znamena, ze ked pri SQL sa musi dana tabulka (a viac tabuliek) nacitat a drzat kompletne v pamati (aj ked vacsina dat z tabulky bude ignorovana), u neo4j sa najde ten jeden konkretny bod, a potom uz len data najblizsie k nemu podla dotazu.

v praxi to znamena, ze je to vhodne ako rozumny storage pre socialne siete, pre kyberku, pre vztahy medzi slovami v ramci nejakeho jazyka, pre data mining ak chceme hladat vztahy medzi entitami, pre vsetko, co akokolvek javi nejaku vztahovu siet.
nie je to vhodne pre fulltext data, ako napriklad indexovanie clankov atd. ako priklad u kyberky by to znamenalo, ze vsetky nody a uzivatelia sa drzia v neo4j, ale konkretny obsah nod by bol nacitavany z ineho uloziska.




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rooter
 rooter      15.02.2017 - 15:06:22 , level: 1, UP   NEW
https://github.com/BloodHoundAD/BloodHound/wiki

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ulkas
 ulkas      15.02.2017 - 09:41:56 , level: 1, UP   NEW
AllegroGraph is a closed source triplestore which is designed to store RDF triples, a standard format for Linked Data.[2] AllegroGraph is currently in use in Open source projects,[3] commercial projects[4][5][6][7] and Department of Defense projects.[8] It is also the storage component for the TwitLogic project[9] that is bringing the Semantic Web to Twitter data.[10]


AllegroGraph® is a modern, high-performance, persistent graph database. AllegroGraph uses efficient memory utilization in combination with disk-based storage, enabling it to scale to billions of quads while maintaining superior performance. AllegroGraph supports SPARQL, RDFS++, and Prolog reasoning from numerous client applications.
http://franz.com/agraph/allegrograph/
http://allegrograph.com/
NewFranz-w-tagline2.png

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ulkas
 ulkas      15.02.2017 - 09:39:33 , level: 1, UP   NEW
http://orientdb.com/orientdb/
orientdb_logo1.png
OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine

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ulkas
 ulkas      15.02.2017 - 09:40:25 , level: 2, UP   NEW
OrientDB is the first Multi-Model DBMS with Document & Graph engine. OrientDB can run distributed (Multi-Master), supports SQL, ACID Transactions, Full-Text indexing, Reactive Queries and has a small memory footprint. OrientDB is licensed with Apache 2 license and the development is driven by OrientDB LTD and a worldwide Open Source community. http://orientdb.com
https://github.com/orientechnologies/orientdb

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ulkas
 ulkas      15.02.2017 - 09:38:00 [1K] , level: 1, UP   NEW
https://www.arangodb.com/
Production ready highly available Multi-Model NoSQL database
teaser-multimodel-color-300px.png

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ulkas
 ulkas      15.02.2017 - 09:38:10 (modif: 15.02.2017 - 09:38:27), level: 2, UP   NEW !!CONTENT CHANGED!!
ArangoDB is a native multi-model database with flexible data models for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.
https://github.com/arangodb/arangodb

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ulkas
 ulkas      15.02.2017 - 09:36:55 , level: 1, UP   NEW
a platform for applying graph algorithms without a persistence layer.
http://jgrapht.org/

directed and undirected graphs.
graphs with weighted / unweighted / labeled or any user-defined edges.
various edge multiplicity options, including: simple-graphs, multigraphs, pseudographs.
unmodifiable graphs - allow modules to provide "read-only" access to internal graphs.
listenable graphs - allow external listeners to track modification events.
subgraphs graphs that are auto-updating subgraph views on other graphs.
all compositions of above graphs.


https://github.com/jgrapht/jgrapht

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ulkas
 ulkas      15.02.2017 - 09:31:47 , level: 1, UP   NEW
janusgraph.png
JanusGraph is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. JanusGraph is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.

In addition, JanusGraph provides the following features:

Elastic and linear scalability for a growing data and user base.
Data distribution and replication for performance and fault tolerance.
Multi-datacenter high availability and hot backups.
Support for ACID and eventual consistency.
Support for various storage backends:
Apache Cassandra
Apache HBase
Oracle BerkeleyDB
Support for global graph data analytics, reporting, and ETL through integration with big data platforms:
Apache Spark
Apache Giraph
Apache Hadoop
Support for geo, numeric range, and full-text search via:
ElasticSearch
Solr
Lucene
Native integration with the TinkerPop graph stack:
Gremlin graph query language
Gremlin graph server
Gremlin applications
Open source under the Apache 2 license.

https://github.com/JanusGraph/janusgraph/
http://janusgraph.org/

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ulkas
 ulkas      15.02.2017 - 09:28:55 (modif: 15.02.2017 - 09:29:23), level: 1, UP   NEW !!CONTENT CHANGED!!
Graph Engine
= RAM Store + Computation Engine + Graph Model
Graph Engine (GE) is a distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine.

The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set.

The capability of fast data exploration and distributed parallel computing makes GE a natural large graph processing platform. GE supports both low-latency online query processing and high-throughput offline analytics on billion-node large graphs.
https://www.graphengine.io/
overview.png
https://github.com/Microsoft/GraphEngine

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ulkas
 ulkas      15.02.2017 - 09:27:33 , level: 1, UP   NEW
Trinity is a general purpose distributed graph system over a memory cloud. Memory cloud is a globally addressable, in-memory key-value store over a cluster of machines. Through the distributed in-memory storage, Trinity provides fast random data access power over a large data set. With the power of fast graph exploration and distributed parallel computing, Trinity supports both low-latency online query processing and high-throughput offline analytics on billion-node scale large graphs.
https://www.microsoft.com/en-us/research/project/trinity/
https://www.microsoft.com/en-us/research/publication/trinity-a-distributed-graph-engine-on-a-memory-cloud/

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ulkas
 ulkas      15.02.2017 - 09:24:38 , level: 1, UP   NEW
Sometimes the relationships between the data you've gathered are more important than the data itself. That's when a graph processing system comes in handy. It's an important but often poorly understood method for exploring how items in a data set are interrelated. Microsoft's been exploring this area since at least 2013, when it published a paper describing the Trinity project, a cloud-based, in-memory graph engine. The fruits of the effort, known as the Microsoft Graph Engine, are now available as an MIT-licensed open source project as an alternative to the likes of Neo4j or the Linux Foundation's recently announced JanusGraph. Microsoft calls Graph Engine (GE) as "both a RAM store and a computation engine." Data can be inserted into GE and retrieved at high speed since it's kept in-memory and only written back to disk as needed. It can work as a simple key-value store like Memcached, but Redis may be the better comparison, since GE stores data in strongly typed schemas (string, integer, and so on). How does all this shape up against the leading open source graph database, Neo4j? For one, Neo4j has been in the market longer and has an existing user base. It's also available in both an open source community edition and a commercial product, whereas GE is only an open source project right now

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ulkas
 ulkas      04.11.2016 - 10:16:59 , level: 1, UP   NEW
http://neo4j.com/graphgist/8173017/

In this Graph Gist, I’m using k-NN with cosine similarity ^[7]^ as the similarity metric to calculate movie recommendations. I wanted a fun data set, so I asked people on Twitter and bothered a few people via email to fill out this form. Using their movie ratings, I’ll calculate the cosine similarity between each person. I’ll then calculate movie recommendations for a person’s unrated movies based on an average rating from that person’s k-nearest neighbors. My methodology will be explained in detail throughout.

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ulkas
 ulkas      22.09.2016 - 11:01:01 , level: 1, UP   NEW
GraphQL is a query language for APIs. Its purpose is to provide a complete description of the data in your API, which can then be used by clients to ask for specific data from the API. A GraphQL query is a string that is sent to a server to be interpreted and fulfilled, which then returns JSON back to the client. The developers differentiate the way GraphQL works as handling data not in terms of resource URLs, secondary keys, or join tables; rather as a graph of objects and the models ultimately used in apps like NSObjects or JSON.
http://www.i-programmer.info/news/90-tools/10095-graphql-leaves-tech-preview.html



0000010100063540000635420818890808190019
ulkas
 ulkas      27.07.2016 - 09:41:06 (modif: 27.07.2016 - 09:47:49), level: 1, UP   NEW !!CONTENT CHANGED!!
dnes akcia free book:
https://www.packtpub.com/packt/offers/free-learning

Use R's powerful graphing capabilities to design and create professional-level graphics
Learn how to use Base R to analyze your data and generate statistical graphs
Create attractive graphics using advanced functions such as qplot and ggplot for research and analysis
A step-by-step guide, packed with examples using real-world data sets that can prove helpful to R programmers


stiahnut sa to da tu:
https://kyberia.sk/id/8190026

0000010100063540000635420818890808188896
SYNAPSE CREATOR
 ulkas      25.07.2016 - 10:04:40 (modif: 25.07.2016 - 10:05:17), level: 1, UP   NEW  HARDLINK !!CONTENT CHANGED!!
https://neo4j.com/blog/neo4j-world-healthcare-part-2

healthcare-connections-lobbyists-graph.png

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SYNAPSE CREATOR
 Harvie      12.12.2010 - 03:35:15 (modif: 13.12.2010 - 14:06:56), level: 1, UP   NEW  HARDLINK !!CONTENT CHANGED!!
(nejen) Moje poznamky o praci s grafama v PgSQL.
Nechci si je syslit pro kyberia.cz, treba nekoho budou inspirovat...
A naopak pokud je mezi vami PostgreSQL odbornik, nebojte se inspirovat me :-)

Kyberka uz davno prerostla detskou ohradku MySQL a je potreba se porozhlidnout po necem novym (to na kyberia.cz taky delame). Ja osobne sem vyzkousel spoustu NoSQL databazi (docela me zaujal Riak a myslim si, ze ma do velmi vzdaleneho budoucna potencial), probihali dlouhe diskuze a hadky u piva, zbourali sme nekolik hospod a jeden kostel bylo po nasi diskuzi nutne znovu vysvetit, ale nakonec jsme zjistili, ze vsechny tyhle DB rychlokvasky zatim funguji i pres neutuchajici a temer psychedelicke nadseni svych vyvojaru spise teoreticky nez v praxi a tak jsme zkoncili u stareho dobreho osvedceneho PostgreSQL.

PostgreS forum: https://kyberia.sk/id/4999650/