![]() MongoDB needs enough RAM to hold your working set in memory. And, if you haven’t, definitely try sharding for horizontal scaling. Don’t do joins (embedding is preferable). It depends on what you are and aren’t doing already. Queries without indexes depend on collection size and machine specs, etc. Primary key or index queries should take just a few milliseconds. MongoDB is a distributed database by default, which allows for expansive horizontal scalability without any changes to application logic. ![]() If you only have a few minutes to spare, this quick performance FAQ might be useful:Īd hoc queries, indexing, and real time aggregation provide powerful ways to access data. Running MongoDB on Atlas, the fully managed, global cloud database service Starting your first project as a seasoned MongoDB developer. While anyone interested in document database platforms could learn something from this post, you’ll probably find this information particularly useful if you’re: Please keep in mind that the best practices we are going to cover are not exhaustive (that would require a much longer post). In this post, we’ll focus on how to achieve performance at scale using MongoDB by looking at: Performance issues may indicate that the database is not working as hard as it could and that specific optimizations could lead to better performance. With its JSON-like documents, MongoDB is notable for horizontal scaling and load balancing, which offers developers an excellent balance of customization and scalability.īut like any high-performance tool, MongoDB performs best in the hands of an expert who knows what they’re doing. MongoDB is the premier NoSQL document database for modern developers working on high-performance applications.
0 Comments
Leave a Reply. |