From a totally new person who was has only basic SQL and found it quite intimidating - very simply and patiently explained. Thanks Ryan. Please can you confirm if they're more videos in this series?
Ryan Boyd from this point even short explanations in Notion will be sufficient - it's fast and easy to put info in Notion and easy to digest later. Like step by step knowledge building series of pieces. May be even with RemNote cards for better learning. I guess I want too much at this point :-)
this was the last of the series. In the meantime we have a few newer series you can watch: Discover Aura: ua-cam.com/video/qdBaJyGxGig/v-deo.html Neo4j Live: ua-cam.com/video/Lr3v22gWixc/v-deo.html
We have lots of video content. 710 videos over a few years. These videos are a variety of types of content though: online meetups (a few times a month), webinars (a few times a month), screencasts, conference talks, interviews, etc. As for this particular series, we are hoping to continue with another few episodes over the next month or so. Our team also just launched an APOC video series too just yesterday!
Hi, this was the last episode of this series. We have new series on AuraDB ( ua-cam.com/video/JUF4-zPskhE/v-deo.html ) or Graph Data Science ( ua-cam.com/video/Niys6g6NFfw/v-deo.html ) for you to watch!
1) When you want a more natural query language to use for querying relationships. Cypher is often cited as being much preferred to SQL for these types of queries. 2) When you want faster performance querying relationships. SQL databases will use index lookups for each JOIN operation. They're very expensive when you're performing many JOINs in the same query. Alternatively, Neo4j stores the relationships at write time, and allows traversing over these relationships via simple pointer arithmetic (sometimes referred to as 'index-free adjacency), which is much more performant and allows you to execute queries with 'many hops' in real-time. This isn't typically possible with SQL JOINs unless you denormalize all your data, but then you lose a lot of other benefits of the database. 3) When you want a schema-optional environment for working with highly connected data. Many developers feel constrained by needing to specify a strict schema up front in SQL databases. We have hundreds of enterprise customers and tens of thousands of other developers who have found these to be good reasons to invest time in learning Neo4j. Of course, if you're happy with your current tech stack and don't have any problems you're trying to solve, then there's no need to learn anything new.
I really wish you had introduced some detail into this introduction such as importing a 10k CSV file and showing me something concrete. We can all index at write time to trade for query time look-ups. I still don't see why you think that's special.
Good series. As a SQL convert, you are making the conversion easy...nice job!
Patiently waiting for the next episode
The logic operation capabilities are just amazing! I like :-)
Great.
Thanks lots for this useful helpful series. Superb!
Thank you for the wonderful series its just amazing....!
From a totally new person who was has only basic SQL and found it quite intimidating - very simply and patiently explained. Thanks Ryan. Please can you confirm if they're more videos in this series?
Good stuff, thank you for the nice video series. I'd love to see more, keep up the good work!
Thanks Kai!
Ryan Boyd from this point even short explanations in Notion will be sufficient - it's fast and easy to put info in Notion and easy to digest later. Like step by step knowledge building series of pieces. May be even with RemNote cards for better learning. I guess I want too much at this point :-)
Thanks for the video.
FYI, looks like there is a slight mistake in the regex expression. It should have been '^K.+' for 'Starts with..'
also on the regular expression, the .+ does not mean zero or one character, it means at least one character
K followed by zero or one character would look like "K.?"
Pretty neat series!! Great way to start of with graph DB
Thanks, 10:24 what is it 'a.name'? 'a' is a person?
Sorry, i don not speak English very well
Thank you for you videos and training support!
Good Series , however I am not able to find next videos of this series
this was the last of the series. In the meantime we have a few newer series you can watch:
Discover Aura: ua-cam.com/video/qdBaJyGxGig/v-deo.html
Neo4j Live: ua-cam.com/video/Lr3v22gWixc/v-deo.html
anyone else pleased by the matrix references? APOC vs Cypher?
Please try putting important links in the description next time. It would be much appreciated.
@Ryan Boynd sir 7th episode is released in you tube?
This is the last of this series! Maybe our AuraDB Live Stream series is interesting for you to watch next: ua-cam.com/video/DOel7oJctwk/v-deo.html
Very good series! Thank you!
This Neo4j is awesome!
Keep it up :) how regularly do you guys do these?
We have lots of video content. 710 videos over a few years. These videos are a variety of types of content though: online meetups (a few times a month), webinars (a few times a month), screencasts, conference talks, interviews, etc.
As for this particular series, we are hoping to continue with another few episodes over the next month or so. Our team also just launched an APOC video series too just yesterday!
where is the 7th episode video i am not getting it ?
Hi, this was the last episode of this series. We have new series on AuraDB ( ua-cam.com/video/JUF4-zPskhE/v-deo.html ) or Graph Data Science ( ua-cam.com/video/Niys6g6NFfw/v-deo.html ) for you to watch!
Please upload more :)
I've watched all these and I'm still in the dark as to why I should invest time in Neo4j
1) When you want a more natural query language to use for querying relationships. Cypher is often cited as being much preferred to SQL for these types of queries.
2) When you want faster performance querying relationships. SQL databases will use index lookups for each JOIN operation. They're very expensive when you're performing many JOINs in the same query. Alternatively, Neo4j stores the relationships at write time, and allows traversing over these relationships via simple pointer arithmetic (sometimes referred to as 'index-free adjacency), which is much more performant and allows you to execute queries with 'many hops' in real-time. This isn't typically possible with SQL JOINs unless you denormalize all your data, but then you lose a lot of other benefits of the database.
3) When you want a schema-optional environment for working with highly connected data. Many developers feel constrained by needing to specify a strict schema up front in SQL databases.
We have hundreds of enterprise customers and tens of thousands of other developers who have found these to be good reasons to invest time in learning Neo4j.
Of course, if you're happy with your current tech stack and don't have any problems you're trying to solve, then there's no need to learn anything new.
I really wish you had introduced some detail into this introduction such as importing a 10k CSV file and showing me something concrete.
We can all index at write time to trade for query time look-ups. I still don't see why you think that's special.
12:38