Neil eifrem, CEO of neo4j, interprets the chart data platform and leads the development of database in the next decade

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Neo4j CEO Emil Eifrem Decipher graph data platform will lead the development of database in the next decade

     The content of the article comes from Neo4j Community experts jennifer Share , Original address Neo4j CEO Emil Eifrem Decipher graph data platform will lead the development of database in the next decade . The following is the full text ：

     Sprout in 20 century 60 The database technology of the s did not become popular in the just rising decade . In the past ten years , The information world is developing rapidly , Faced with extreme complexity 、 interconnection 、 dynamic 、 A torrent of changing data , Database platforms have sprung up , The choices in the market have increased to 350 Multiple . these years , The database market is growing every year 5 % to 6% The speed of rapid expansion , The market volume will be in the future 4 To 5 The year is expected to change from the present 500 US $billion climbed to 1,000 Billion dollars .

     In the past two years, , The development trend of database industry presents three characteristics .

     The first is integration , With the large-scale innovation of new data , The rapidly expanding database market once again presents an integrated situation , Hundreds of database vendors are gradually classified as including document databases 、 Graph database 、 Time series database 、NewSQL Four new and stable database camps, including database . In different subdivisions , Only a limited number of companies are singing loudly on the way to lead , As shown in the figure Neo4j And documentation MongoDB.

     second , The shift to the cloud has become a long-term trend of the entire industry .2017 Around, some large cloud providers and independent cloud providers began to emerge . Although progress has slowed down due to data gravity and regulatory factors , Now this trend is like a rainbow again . To a large extent, the transfer of data to cloud services has become a driving factor for the development of database platforms .

     Third , Data scientists are in the ascendant . As a whole , Data scientists don't like databases , They prefer data . The graph database is an exception , More and more data scientists are interested in graph databases . Data scientists use graphical algorithms to process data , Then input the data into the machine learning pipeline through the diagram , Thus, it provides relational signals for machine learning model and prediction . thus , The graph database becomes the core part of the machine learning pipeline .

     Take the supply chain for example ,10 Years ago, supply chain application was not the best use case for graph database . Because at that time, any manufacturing company that produced physical products might only have one 2 To 3 Three levels of supply chain , Relational database can fully meet the needs of enterprises . If you need to analyze , Join in 2 to 3 Just one node .

     today , Manufacturing enterprises not only have a wide range of businesses , Across different continents , But also to deal with one after another emergencies , Manufacturing enterprises need to understand the impact of this event on the supply chain and even the business , Have the ability to ensure the security of the supply chain , The effective solution is to digitize the supply chain . Now , The data analysis faced by enterprises is no longer 2 to 3 Jump mining times , It is 20、30 even to the extent that 40 Jump mining . The database, especially the graph database that performs well in multiple jumps, has become an inevitable choice .

     Unlike relational databases , Graph database is centered on the connection mode of things , Emphasize the relationship between data , It regards the connection between data as equally important as the data itself . Graph data platform enables users to develop and run applications on graph database , It directly stores relationships and data at the physical level , The operation of accessing data nodes and relationships can be completed with linear time complexity . In general PC The test results on the machine show that ,Neo4j The query engine of graph database can easily traverse millions of relationships in one second / edge .

     In the next decade , It will be a decade for the graph data platform to become the mainstream and shine , This has not only caused industry experts to rethink the graphics technology , It is also a blessing for developers . Developer driven is Neo4j Culture ,Neo4j The success of is inseparable from the construction of developer ecology .Neo4j Pay attention to the investment in developers and strive to serve them , In addition to regular training 、 Meetings and other activities , Also published a large number of corresponding technical books , To help developers grow .