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Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL. Join this webinar to learn why companies are shifting away from RDBMS towards graphs to unlock the business value in their data relationships
As the only NoSQL database category that prioritizes relationships, graph databases provide all the flexibility of a NoSQL database with optimized performance for connected data. This webinar will walk you through how to model your data as a graph. We will demonstrate how to avoid pitfalls early on and how to optimize your model for answering questions as Cypher queries.
While the Rio 2016 Olympics are winding down and the final medals are being handed out, we thought we would share a bit of work that was done recently by Rik Van Bruggen to explore a really interesting dataset in Neo4j.
Based on an original public dataset by the UK newspaper The Guardian, Rik completed the medallist dataset to contain over 30,000 Olympians between 1896 and 2012. He created a graph model, loaded the data, and wrote a bunch of example queries that yielded some very interesting results. Join us for this 30 minute webinar where we’ll take you through this great Olympian graph and take the data for a spin yourself afterwards.
We are one of the eminent sourcing agent of Bedding, Ladies Garments, Coir Products, Floor Covering, Decorative Glass, Wooden Furniture, Metal Handicraft, Lighting and Home Furnishing.
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL. Join this webinar to learn why companies are shifting away from RDBMS towards graphs to unlock the business value in their data relationships
As the only NoSQL database category that prioritizes relationships, graph databases provide all the flexibility of a NoSQL database with optimized performance for connected data. This webinar will walk you through how to model your data as a graph. We will demonstrate how to avoid pitfalls early on and how to optimize your model for answering questions as Cypher queries.
While the Rio 2016 Olympics are winding down and the final medals are being handed out, we thought we would share a bit of work that was done recently by Rik Van Bruggen to explore a really interesting dataset in Neo4j.
Based on an original public dataset by the UK newspaper The Guardian, Rik completed the medallist dataset to contain over 30,000 Olympians between 1896 and 2012. He created a graph model, loaded the data, and wrote a bunch of example queries that yielded some very interesting results. Join us for this 30 minute webinar where we’ll take you through this great Olympian graph and take the data for a spin yourself afterwards.