List/Grid Tag Archives: MongoDB

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MongoDB “Lightning Fast Aggregation” Challenged with Oracle

What does “Scale” even mean in the context of databases? When talking about scaling, people have jumped to the vendor-induced conclusion that:SQL doesn’t scale NoSQL scalesIt ...
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MongoDB Facts: Lightning speed aggregation

In my previous post, I demonstrated how fast you can insert 50 millions time-event entries with MongoDB. This time we will make use of all that data to fuel our aggregation tests. This ...
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Create a simpe RESTful service with vert.x 2.0, RxJava and mongoDB

A new article after an hiatus of almost half a year. In this article we’ll have quick look at how you can get started with vert.x and more interestingly how you can use RxJava ...
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MongoDB Facts: 80000+ inserts/second on commodity hardware

While experimenting with some time series collections I needed a large data set to check that our aggregation queries don’t become a bottleneck in case of increasing data loads. We ...
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Spring Data MongoDB cascade save on DBRef objects

Spring Data MongoDB by default does not support cascade operations on referenced objects with @DBRef annotations as reference says: The mapping framework does not handle cascading saves. ...
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Auditing Entities in Spring Data MongoDB

Spring Data MongoDB 1.2.0 silently introduced new feature: support for basic auditing. Because you will not find too much about it in official reference in this post I will show what ...
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MongoDB: GridFS remove method deletes all files in bucket

Some time ago we ran into strange behaviour of MongoDB’s GridFS which caused me creating a Bug Ticket for the MongoDB Java driver. Today I found the link to the bug ticket in ...
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Optimistic locking retry with MongoDB

In my previous post I talked about the benefit of employing optimistic locking for MongoDB batch processors. As I wrote before, the optimistic locking exception is a recoverable one, ...
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MongoDB optimistic locking

When moving from JPA to MongoDb you start to realize how many JPA features you’ve previously taken for granted. JPA prevents “lost updates” through both pessimistic and optimistic ...
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MongoDB and Web applications

Today’s era is when data grows at very huge scale. Data storage is not a problem, yes but the way it gets structured and stored may increase or decrease the seek time for needed data ...
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