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Introduction of Bitnine - Business Summary
Big Data Platform Technology Service through Graph Database
Open Source Database Solution and ServicesAgensGraph and AgensSQL
Intuitive Big Data Visualization Solution through Graph ModelingOptimized Visualization for IoT
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Introduction of Bitnine - Summary
Bitnine Korea HQ Bitnine US R&D Center
1) Multi-Model Database Solution R&D (AGENS solutions)
2) Government project execution & Technology integration
3) Big Data Platform Technology Service through Graph Database
4) Open source database implementation
5) Intuitive Data Visualization Solution through Graph Modeling
Main Business
Area
Bitnine Employee number : 31 (as of Feb. 2017)
Bitnine US Marketing
Foundation: Oct. 2013
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Introduction of Bitnine - Business Summary
▪ The first integrated database package and its extension modules in Korea based on PostgreSQL ▪ The core member and the Gold Sponsor of global PostgreSQL communities▪ Customers : Woori Investment Securities, LG CNS, Government Complex Data Center, Postech,
Dongjin Semichem, Samsung Display and etc.
▪ AgensGraph V 1.0 release in Jan. 2017.▪ AgensGraph is the first multi-model graph database management solution in Korea▪ Use Case : Recommendation Engine, Fraud Detection, Geo systems, Master Data Management,
Network and Data Center Management, Authorization and Access Control, Bio-Informatics
▪ Big Graph will be processed and executed based on Big Data platform and will be customized and developed through the integration of the graph database.
▪ Partnership : IBM, EMC, Cloudera, Neo4j▪ ISV : Cloudera, Hortonworks, Cyram, Linkurious, Cambridge Intelligence
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SELECT friend.id, count(comments)FROM (MATCH (:person {id: 1})-[:knows*1..2]->(friend) RETURN friend.id AS id) friend, -- Cypher subquery comment -- Relational tableWHERE friend.id = comment.creatorId AND comment.createdate > '2016.1.1';
MATCH (n:dev)WHERE n.year::int < (SELECT year FROM history WHERE event = 'AgensGraph')RETURN properties(n) AS n;
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Start person
New post
tag
friend
friend2 Old post
Pattern 1
Pattern 2
Find pattern1 which does not have pattern2
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●MATCH (person:Person {id:{1}})-[:KNOWS]-(:Person)<-[:HAS_CREATOR]-(post:Post)-[:HAS_TAG]->(tag:Tag)WHERE post.creationDate >= {2} AND post.creationDate < {3}OPTIONAL MATCH (tag)<-[:HAS_TAG]-(oldPost:Post)-[:HAS_CREATOR]->(:Person)-[:KNOWS]-(person)WHERE oldPost.creationDate < {2}WITH tag, post, length(collect(oldPost)) AS oldPostCountWHERE oldPostCount=0RETURN tag.name AS tagName, length(collect(post)) AS postCountORDER BY postCount DESC, tagName ASCLIMIT 20;
Pattern 1
Pattern 2Find pattern1 which does not have pattern2
● But this query takes too long because it searches Pattern2 for each occurrences of Pattern1● If # of Pattern1 is n and # of Pattern2 is m, then n X m traversals are needed!!
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●SELECT tagname, count(distinct postid) AS postcount FROM ( SELECT NewPost.tag AS tagname, NewPost.postid AS postid, count(distinct OldPost.postid) AS oldPostCount FROM ( MATCH (person:Person {id:$1})-[:KNOWS]->()<-[:hasCreatorPost]-(post:Post)-[:hasTagPost]->(tag:Tag) WHERE post.creationDate >= $2 AND post.creationDate < $3 RETURN post.id AS postid, tag.name AS tag) NewPost LEFT JOIN ( MATCH (person:Person {id:$4})-[:KNOWS]->()<-[:hasCreatorPost]-(post:Post)-[:hasTagPost]->(tag:Tag) WHERE post.creationDate < $2 RETURN post.id AS postid, tag.name AS tag) OldPost ON NewPost.tag = OldPost.tag GROUP BY NewPost.tag, OldPost.postid) AWHERE oldPostCount = 0 GROUP BY tagname ORDER BY postcount DESC, tagname ASC LIMIT 20;
Pattern 1
Pattern 2
Find pattern1 which does not have pattern2
● This query find Pattern1 and Pattern2 respectively, and left join them● n + m traversals are needed not n X m traversals !!
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