Do you think nosql can keep up when doing arbitrary analysis of structured data? I’m under the impression that for real data analysis work you’re going to want a query/access optimizer to help you out.
Also, I’m interested to hear how orientdb performs returning near petabyte result sets.
Ken has a long history around computers starting with early Commodore PETs and VIC-20s. He is a MongoDB Certified Developer and lives in Oregon with his wife and three children. You can find him mo...
I think it all depends on your application and data design. NoSQL can be incredibly fast for processing but to get the most "bang for your buck" schemas need to be designed differently than they are in a SQL world. It's not a bad thing. It's just a different data modeling style.
In terms of OrientDB performance specifically, it can handle large loads. However, like I just said, the data model is important for top performance. There are many resources available on NoSQL schema design that are well worth the time to read.
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Do you think nosql can keep up when doing arbitrary analysis of structured data? I’m under the impression that for real data analysis work you’re going to want a query/access optimizer to help you out.
Also, I’m interested to hear how orientdb performs returning near petabyte result sets.
I think it all depends on your application and data design. NoSQL can be incredibly fast for processing but to get the most "bang for your buck" schemas need to be designed differently than they are in a SQL world. It's not a bad thing. It's just a different data modeling style.
In terms of OrientDB performance specifically, it can handle large loads. However, like I just said, the data model is important for top performance. There are many resources available on NoSQL schema design that are well worth the time to read.