There is a wide variety of indexes available in PostgreSQL. While most are common in almost all databases, there are some types of indexes that are more specific to PostgreSQL. For example, GIN indexes are helpful to speed up the search for element values within documents. GIN and GiST indexes could both be used […]Read more
In this article I’m going to talk about partial and sparse indexes in MongoDB® and Percona Server for MongoDB®. I’ll show you how to use them, and look at cases where they can be helpful. Prior to discussing these indexes in MongoDB in detail, though, let’s talk about an issue on a relational database like […]Read more
Like MySQL, having too many indexes on a MongoDB collection not only affects overall write performance, but disk and memory resources as well. While MongoDB holds predictably well in scaling both reads and writes options, maintaining a heathly schema design should always remain a core character of a good application stack.
Aside from knowing when […]
In this blog post, we will walk through PMM-Query Analytics for MongoDB. We will see how to analyze MongoDB query performance; review the initial parameters that we need to check; and find out how to compare MongoDB query performance with and without indexes with the help of EXPLAIN plan.
The Percona Monitoring and Management QAN (PMM-QAN) dashboard […]
In this blog post, we will talk about MongoDB indexing, and the different types of indexes that are available in MongoDB.
Note: We are hosting a webinar on July 12, 2017, where I will talk about MongoDB indexes and how to choose a good indexing plan.
MongoDB is a NoSQL database that is document-oriented. NoSQL databases […]
Talking with Percona Live attendees last year I heard a couple of common themes. First, people told me that there is a lot of great advanced content at Percona Live but there is not much for people just starting to learn the ropes with MySQL. Second, they would like us to find a way […]Read more
In this post, I’d like to discuss some performance problems recently mentioned about MongoDB’s embedded arrays, and how TokuMX avoids these problems and delivers more consistent performance for MongoDB applications.
In “Why shouldn’t I embed large arrays in my documents?“, Asya Kamsky of MongoDB explains why you shouldn’t embed large arrays in your MongoDB documents. It’s […]
We just released version 1.4.0 of TokuMX, our high-performance distribution of MongoDB. There are a lot of improvements in this version (release notes), the most of any release yet. In this series of blog posts, we describe the most interesting changes and how they’ll affect users.
MongoDB doesn’t have a “primary key” the way SQL […]
Before creating a unique index in TokuMX or TokuDB, ask yourself, “does my application really depend on the database enforcing uniqueness of this key?” If the answer is ANYTHING other than yes, do not declare the index to be unique. Why? Because unique indexes may kill your write performance. In this post, I’ll explain […]Read more
In my three previous MongoDB blogs I wrote about our implementation of Fractal Tree(R) indexes on MongoDB, showing a 10x insertion performance increase, a 268x query performance increase, and a comparison of covered indexes and clustered indexes. These benchmarks show the difference that rich and efficient indexing can make to your MongoDB workload.
Given the […]