In my two previous blogs I wrote about our implementation of Fractal Tree Indexes on MongoDB, showing a 10x insertion performance increase and a 268x query performance increase. MongoDB’s covered indexes can provide some performance benefits over a regular MongoDB index, as they reduce the amount of IO required to satisfy certain queries. In […]Read more
Last week I wrote about our 10x insertion performance increase with MongoDB. We’ve continued our experimental integration of Fractal Tree® Indexes into MongoDB, adding support for clustered indexes. A clustered index stores all non-index fields as the “value” portion of the index, as opposed to a standard MongoDB index that stores a pointer to […]Read more
The challenge of handling massive data processing workloads has spawned many new innovations and techniques in the database world, from indexing innovations like our Fractal Tree® technology to a myriad of “NoSQL” solutions (here is our Chief Scientist’s perspective). Among the most popular and widely adopted NoSQL solutions is MongoDB and we became curious […]Read more
Another thing I find interesting about MongoDB is its approach to Durability, Data Consistency and Availability. It is very relaxed and will not work for some applications but for others it can be usable in current form. Let me explain some concepts and compare it to technologies in MySQL space.
First I […]