In this first installment of a new, detailed series for MongoDB developers to learn Couchbase by comparison, take a look at the architecture of each.
Join the DZone community and get the full member experience. With this article on MongoDB to Couchbase comparison, I’m starting a new, detailed series for MongoDB developers to learn Couchbase by comparison. Two years ago, I wrote a single high-level comparative article on MongoDB and Couchbase. I recommend you read that for a bird’s view comparison. Both MongoDB and Couchbase have done multiple major releases since then, and developers need a deeper treatment of topics. As developers know, the devil is in the details:-) This series will be similar to the series for Oracle developers to learn Couchbase by comparison, but for MongoDB developers. Here are the topics for the planned articles. Developers work on databases using multiple sets of abstraction: data models, APIs, and languages. We refer to RDBMS as SQL databases: SQL is the language. Couchbase has N1QL and MongoDB has MQL. We’ll start with that high-level language and feature comparison to get you going. Here’s the high-level comparison between MongoDB’s MQL model versus Couchbase’s N1QL model for objects, language, and query processing. We’ll discuss these in detail in the rest of this blog series. MongoDB and Couchbase have many things in common. Both are modern NoSQL distributed databases, use the JSON model, have high-level query languages with support for select-join-project operations, have secondary indexes, have an optimizer that chooses the query plan automatically, and support intra-cluster and inter-cluster replication. As you’d expect, there are differences. Some are more significant than others. Couchbase is designed to be distributed from the get-go. For example, the data containers’ buckets and collections are always distributed.
