9 ms·

Nah, not really practical in a database with millions of nodes and millions or billions of edges (which both the Directed Edge DB and neo4j support). The query

by wheels 18y ago

Nah, not really practical in a database with millions of nodes and millions or billions of edges (which both the Directed Edge DB and neo4j support). The query would finish, but not in in the amount of time that you'd need for a lot of graph applications.

Retric 18y ago
For up to million nodes this would probably take less than 1 second if it's kept in memory. Anyway, if you want to query this 50 times a second on a huge DB write custom code, or use Directed Edge DB etc. My point was you can still do it on all SQL databases in a reasonable amount of time using basic SQL. SQL trades speed for flexibility and it's incredibly flexible. Computers are insanely fast and they have incredible amounts of storage. Problems that used to take expensive custom HW tend to migrate to the generic solution which why SQL is still the default after all these years. If anything I suspect most problems that take clusters today will quickly migrate to a single machine solution. Google might have a 50,000 node cluster, but web search is probably being consolidated to fewer machines over time. Google keeps adding other services like gmail that use their cluster, but the searchable internet is just not growing that fast over the next 20 years. Edit: A graph of every human relationship in the world is still finite. Rendering a complex 3D model can take limitless amount of computational resources but most data centric problems don't really grow. Early on they take huge amount of resources say 1960's era Mainframes but eventual that class of problems fit on your iPhone.
- rw 18y ago
  > "but the searchable internet is just not growing that fast over the next 20 years." Please defend that statement.
  - Retric 18y ago
    To "keep up" with computing power, the searchable internet would need to grow at more than 50% per year which it's not. Now we could argue that Google is going to add some AI that does image search though actual sound / images / movies etc, but IMO it's all still going to be text in 20 years. So, it's a question of how much text is going to be on the internet over the next 20 years. Facebook is already popular enough that there are not enough people in the world for it to grow 50% / year much longer, so it comes down to what % of all human interactions are going to take place online. Granted things change, but I don't see the average person in south Africa is going to start tweeting 10 hours a day within 20 years. We could argue that more companies are going to place their information online but many already do that and it's not growing at 50% / year. It all comes down to the limits of exponential growth, computers are not going to hit hard limits within 20 years and few things can keep up with that level of growth.

by wheels 18y ago

Retric 18y ago

For up to million nodes this would probably take less than 1 second if it's kept in memory. Anyway, if you want to query this 50 times a second on a huge DB write custom code, or use Directed Edge DB etc. My point was you can still do it on all SQL databases in a reasonable amount of time using basic SQL. SQL trades speed for flexibility and it's incredibly flexible. Computers are insanely fast and they have incredible amounts of storage. Problems that used to take expensive custom HW tend to migrate to the generic solution which why SQL is still the default after all these years. If anything I suspect most problems that take clusters today will quickly migrate to a single machine solution. Google might have a 50,000 node cluster, but web search is probably being consolidated to fewer machines over time. Google keeps adding other services like gmail that use their cluster, but the searchable internet is just not growing that fast over the next 20 years. Edit: A graph of every human relationship in the world is still finite. Rendering a complex 3D model can take limitless amount of computational resources but most data centric problems don't really grow. Early on they take huge amount of resources say 1960's era Mainframes but eventual that class of problems fit on your iPhone.

rw 18y ago
> "but the searchable internet is just not growing that fast over the next 20 years." Please defend that statement.
- Retric 18y ago
  To "keep up" with computing power, the searchable internet would need to grow at more than 50% per year which it's not. Now we could argue that Google is going to add some AI that does image search though actual sound / images / movies etc, but IMO it's all still going to be text in 20 years. So, it's a question of how much text is going to be on the internet over the next 20 years. Facebook is already popular enough that there are not enough people in the world for it to grow 50% / year much longer, so it comes down to what % of all human interactions are going to take place online. Granted things change, but I don't see the average person in south Africa is going to start tweeting 10 hours a day within 20 years. We could argue that more companies are going to place their information online but many already do that and it's not growing at 50% / year. It all comes down to the limits of exponential growth, computers are not going to hit hard limits within 20 years and few things can keep up with that level of growth.