12 Months with MongoDB

Alright, so, I fully understand the scalability reasons for using MongoDB, but I need someone to clearly explain to me when NoSQL would be a better solution than SQL <i>from a development standpoint</i>. Because like someone pointed out, Postgres without fsync can be just as fast.<p>What is the advantage of giving up the ability to use SQL and the associated relational algebra that has long been established in that query language? I'm not asking to start a flame war, I'm sincerely interested. Can someone give me a use case for when NoSQL would have a clear advantage over SQL?

It is kind of odd that speed is the main motivation to switch from MySQL. Horizontal scaling is the usually given reason. From what I have seen Mongo achieves most of its speed by not using fsync by default. There were some slides floating around a while ago that showed Postgres at about the same speed by turning off fsync.

Only had 5 days with MongoDB and I found it a good alternative for persistence of basic data structure in Python, my main concern was something that can $set individual elements of a JSON instead of retrieving the whole doc and modify it.

Dumb question: the author talks about not having to use caching because Mongo has built-in caching. Don't most RDBMSes also have built-in caching?

From the tutorial:<p>SELECT * FROM things WHERE name="mongo"<p>================================================<p>&#62; db.things.find({name:"mongo"}).forEach(printjson); { "_id" : ObjectId("4c2209f9f3924d31102bd84a"), "name" : "mongo" }<p>I am having a hard time finding the benefit of that except you can do it programmatically and not step out of your language of choice and into SQL.<p>I am just looking into this...so maybe the lightbulb will get brighter as I go through the docs for MongoDB.

Has anyone had experience comparing MongoDB and HiveDB from apache? I briefly considered both of them over a year ago before realizing that they weren't quite yet prime time for my application, and I've not had time to look at them since. I'm curious to see how they've evolved in practice.

Great writeup! Couple questions:<p>- I'm curious why querying before a write makes such a big difference. I would have guessed that updating a document that's not in RAM would first load it into RAM, then perform the update. Does the write get applied to disk without loading the page into RAM first? If you do an update to a document that is not in RAM, is it in RAM following the update?<p>- Can you elaborate on the corruption that occurred to both the master &#38; the slave during a DAS failure? We have seen something similar in our deployment (high write volume leading to corruption in both master &#38; slave. required repair to recover. ran on a partially functioning slave during the repair), but were unable to identify the root cause.

Where are the "MongoDB is Web Scale" jokes? crickets. If you are not using MongoDB, you are missing out badly and are probably developing at a much slower rate than someone who is.