Grafdatabase og datadrevne applikationer,en
Oversigt
Moderne dag,,en,datadrevne applikationer,,en,er stort set afhængige af relevant indsigt, der stammer fra de enorme mængder data, de håndterer hver dag,,en,At få bedre indsigt hver gang,,en,applikationerne skal være i stand til at sende komplekse forespørgsler, og databasen skal kunne adressere komplekse forespørgsler,,en,Traditionel,,en,systemer, der er afhængige af SQL, er ikke i stand til at håndtere ekstremt komplekse spørgsmål,,en,Grafdatabaser har været i stand til at løse dette problem, fordi det er afhængig af objekter og forhold mellem objekter,,en,Baseret på denne forudsætning,,en,det er muligt at udtrække dyb indsigt,,en,Brug af grafdatabaser,,en,er stadig begrænset, selvom der er klare tegn på, at det vil spille en vigtig rolle, da virksomheder mere og mere er afhængige af indsigt til at drive deres forretning,,en,Hvad er en grafdatabase,,en,At forstå,,en,grafisk database,,en data-driven applications are largely dependent on relevant insights derived from the enormous volumes of data they handle every day. To gain better insights every time, the applications need to be able to send complex queries and the database should be able to address complex queries. Traditional RDBMS systems that rely on SQL are unable to handle extremely complex queries. Graph databases have been able to solve this problem because it relies on objects and relationships between objects. Based on this premise, it is possible to extract deep insights. The use of graph databases, however, is still limited although there are definite signs that it is going to play an important role as businesses rely more and more on insights to power their business.
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What is a graph database?
To understand graph database, lad os bruge eksemplet herunder,,en,Bill og hans familie planlægger at tage på en ferie til et sted, der tilbyder fantastiske orientalske retter,,en,Han er begyndt at planlægge tidligt, og en af måderne til at finde information er selvfølgelig,,en,Mens oplysningerne fra Google er troværdige og gode,,en,til Bill,,en,det er vigtigt at få så specifik information som muligt,,en,han begynder at spørge sine venner,,en,bekendte og kolleger,,en,Lad os antage, at Bill spørger Ryan,,en,Sheena og John, som er hans primære kontakter og kontaktniveau,,en,Alle tre lover at vende tilbage med information så hurtigt som muligt,,en,Ryan spørger sin ven Greig, der igen spørger sin fætter Martin, der havde været i Bangkok et par gange,,en,Martin anbefaler navnene og detaljerne på alle spisesteder i Bangkok kendt for deres orientalske retter,,en:
Bill and his family are planning to go on a vacation to a place that offers great oriental dishes. He has started planning early and one of the ways to find information is of course, Google. While the information from Google is credible and good, for Bill, it is important to get as specific information as possible. So, he starts asking his friends, acquaintances and colleagues. Let us assume that Bill asks Ryan, Sheena and John who are his primary contacts and contact level 1. All three promise to revert with information as soon as possible. Ryan asks his friend Greig who again asks his cousin Martin who had been to Bangkok a few times. Martin recommends the names and details of all eateries in Bangkok known for their oriental dishes. Oplysningerne videresendes til Bill,,en,Du har lige set et ægte eksempel på en kompleks forespørgsel baseret på genstande og forhold,,en,Grafdatabasen fungerer efter samme princip,,en,Det handler om netværket og objekterne og deres forhold i netværket,,en,grafdatabase er i stand til ekstremt komplekse grafer og giver indsigt, som SQL-forespørgselsbaserede RDBMS-systemer ikke kan,,en,Og det er det unikke salgssted for grafdatabaser,,en,Hvordan fungerer grafisk database,,en,Ovenstående beskrivelse af en grafdatabase skal have givet en idé om de principper, en grafedatabase anvender, når det drejer sig om at søge efter information eller indsigt,,en,det krydser netværket af objekter og relationer baseret på forespørgslen og returnerer resultaterne,,en,Hvis vi tager ovenstående eksempel på Bill,,en.
You have just seen a real-life example of a complex query based on objects and relationships.
The graph database works on the same principle. It is about the network and the objects and their relationships in the network.
Basically, graph database is capable of extremely complex graphs and provide insights which SQL-query based RDBMS systems cannot. And that is the unique selling point about graph databases.
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How does graph database work?
The above description of a graph database must have given some idea about the principles that a graph database applies when it goes about searching for information or insights. Basically, it traverses the network of objects and relationships based on the query and return the results.
If we take the above example of Bill, så hvordan ville en grafdatabase gå ud på sit job,,en,der er mange forhold og knuder i eksemplet,,en,Hvis vi ser afstanden mellem forholdene,,en,det ser ud til at være følgende,,en,Regning =,,en,oprindelsen,,en,Ryan =,,en,Sheena =,,en,John =,,en,Greig =,,en,Martin =,,en,Afstanden mellem oprindelsen,,en,nul,,en,og den knude, der giver informationen, kan være endnu længere i det virkelige liv,,en,Sådan fungerer netværket,,en,Forestil dig en applikation, der sender en forespørgsel baseret på Bills krav,,en,Det ville være noget som nedenunder,,en,Find alle venner, der er forbundet med fem venner, der kan lide orientalsk mad, men som har besøgt Thailand, og som bor inden for,,en,miles fra Dallas,,en,Fort værd,,en,Der er mange grafiske databaser tilgængelige på markedet, og Neo4j er den mest populære blandt dem,,en? Naturligvis, there are a lot of relationships and nodes in the example. If we see the distance of the relationships, it would seem like the following:
Bill = 0 (the origin)
Ryan = 1
Sheena = 1
John = 1
Greig = 2
Martin = 3
The distance between the origin (zero) and the node that provides the information could be even farther in real life. That is how the network works.
Imagine an application sending a query based on Bill’s requirement. It would be something like the below:
Find all friends who are connected with five friends who like oriental food but visited Thailand and who live within 5 miles of Dallas, Fort worth.
There are a lot of graph databases available in the market and the Neo4j is the most popular among them. Neo4j kan tilskrive sin popularitet til de kendsgerninger, at det både er effektivt og open source,,en,når du sender en forespørgsel til Neo4j for at løse Bill's problem,,en,forespørgslen kunne ligne nedenunder,,en,vælg venner og venner af venner,,en,nøgleord for orientalsk mad,,en,nøgleord for Bangkok,,en,rækkefølge efter forholdets dybde,,en,Streng findFriendsQuery =,,en,start n = knude,,en,personer = node,,en,userNode,,en,MATCH p =,,en,person,,en,VEN * 1..2,,en,ven,,en,returner tydelige p rækkefølge efter længde,,en,Baseret på forespørgslen,,en,Neo4j vil søge gennem sit tilgængelige netværk og finde nærmeste kampe,,en,Forskel mellem grafdatabase og relationsdatabase,,en,Det vigtigste punkt, som relationel database og grafdatabase sammenlignes med, er transaktionshastigheden,,en,det er,,en,hvor hurtigt kan det behandle en kompleks forespørgsel på et stort datasæt,,en,For nogle dage siden,,en,Emil Eifrem,,da. So, when you send a query to the Neo4j to solve Bill’s problem, the query could look something like the below:
// select friends and friends of friends, keyword of oriental food, keyword of Bangkok, order by depth of the relationship
String findFriendsQuery = “start n=node(*), person=node({userNode}) MATCH p = (person)-[:FRIEND*1..2]-(friend) return distinct p order by length(p)”;
Based on the query, Neo4j is going to search through its available network and find closest matches.
Difference between graph database and relational database
The main point around which relational database and graph database are compared is speed of transaction, that is, how fast can it process a complex query on a big dataset.
Some days ago, Emil Eifrem, administrerende direktør for Neo Technology firmaet bag Neo4j,,en,målte ydeevnen for både relationelle og grafiske databaser på flere parametre,,en,Forespørgslen var,,en,brugere, hvor hver bruger har,,en,venner eller mere,,en,Find ud af, om den ene bruger er tilsluttet en anden i,,en,eller færre humle,,en,En populær open source relationel database tog,,en,ms for at behandle forespørgslen, mens grafdatabasen blev taget,,en,Når den samme forespørgsel blev kørt på en brugerbase af,,en,grafdatabasen tog 2 ms, mens den relationelle database måtte afbrydes efter et par dage med uendelig behandling,,en,Hovedårsagen til at den relationelle database tog så lang tid at behandle forespørgsler var, at den søgte dataene for hvert sigt, der blev leveret i forespørgslen,,en,Ikke underligt, at det tog lang tid,,en,På større database,,en,det vil tage endnu længere tid,,en,Grafdatabasen,,en, measured the performance of both relational and graph databases on multiple parameters. The query was: i 1000 users with each user having 50 friends or more, find out if one user is connected to another in 4 or fewer hops. The results are given below:
- A popular open-source relational database took 200 ms to process the query while graph database took 2 ms.
- When the same query was run on a user base of 1000000 users, the graph database took 2ms while the relational database had to be aborted after a few days of never-ending processing.
The main reason the relational database was taking such a long time to process queries was that it was searching the data for every term provided in the query. No wonder then that it was taking a long time. On bigger database, it would take even longer. The graph database, på den anden side, ville kun se på poster, der er direkte forbundet med posterne i databasen,,en,Hvis grafdatabasen er tilladt, er et specifikt antal humle,,en,så ville det holde sig nøjagtigt til det,,en,Det var grunden til, at grafikdatabasen relativt let kunne behandle komplekse forespørgsler på enorme datasæt og opnår hurtigere resultater,,en,Casestudier på grafisk database,,en,Der har været mange succesrige applikationer af grafdatabasen i forskellige brancher,,en,De store virksomheder har ført vejen i opbygningen af deres produkter i verdensklasse med grafdatabaseprincipperne,,en,Oprindeligt troede man, at da det handlede om knudepunkter og forhold,,en,visse brancher som de sociale medier kunne drage fordel af dette,,en,andre sektorer såsom online dating,,en,produktion og online jobportaler har også draget fordel af det,,en. If the graph database is allowed a specific number of hops, then it would stick to that exactly. That was the reason graph database was able to process complex queries on huge datasets relatively easily and achieves faster results.
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Case studies on graph database
There have been many successful applications of the graph database in different industries. The big companies have led the way in building their world-class products with the graph database principles. Initially it was thought that since it was about nodes and relationships, certain industries like the social media could benefit from this. Dog, other sectors such as online dating, manufacturing and online job portals have also benefited from it. Nedenfor er et par eksempler,,en,Facebook har med succes brugt grafdatabasen til at opbygge sit produkt i verdensklasse,,en,du er i stand til at søge information ved at gå gennem dit netværk af venner og deres osv,,en,LinkedIn har arbejdet på sin meget publicerede økonomiske graf,,en,Den økonomiske graf planlægger at give passende muligheder for alle dens brugere ved at forbinde brugerne med virksomhederne og deres profiler op til et vist niveau,,en,Anbefalingssystemet,,en,hvilket er et meget vigtigt værktøj for mange online detailhandlere,,en,har brugt grafdatabaseprincipperne til at levere effektive,,en,relevante henstillinger til potentielle forbrugere,,en:
- Facebook has successfully put to use the graph database in building up its world-class product. I dag, you are able to search information by traversing across your network of friends and theirs and so on.
- LinkedIn has been working on its much-publicized Economic Graph. The Economic Graph plans to provide suitable opportunities to all its users by connecting the users with the companies and their profiles up to a certain level.
- The recommendation system, which is a very important tool for many online retailers, has been using the graph database principles to provide effective, relevant recommendations to potential consumers. Anbefalingsmotorer søger dybest set netværket af kunder, der har foretaget lignende køb over en periode og antager, at kunden, der gennemser lignende produkter, vil have den samme smag og præferencer.,,en,For alt potentialet i grafdatabasen,,en,mange virksomheder spiller stadig ind på trenden,,en,det vil vare et stykke tid, før grafdatabasen accepteres bredt,,en,Mens potentialet ved grafdatabase til løsning af komplekse problemer ikke længere er i tvivl,,en,relationen til databasen er ikke truet på nogen måde,,en,Det bedste ved grafdatabasen er, at den kan tilbydes som en open source-teknologi,,en,Det er op til brancherne at udnytte fordelene,,en,Udforsk flere artikler om NoSQL DB,,en,techalpine.com/graph-database-and-data-driven-applications,,en.
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Summary
For all the potential of graph database, a lot of companies are still playing catch up with the trend. So, it will be a while before graph database is widely accepted. While the potential of graph database in solving complex problems is no longer in doubt, the position of relational database is not threatened in any way. The best thing going for graph database is that it can be offered as an open-source technology. It is up to the industries to leverage the benefits.
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