Couchbase Under the Hood

Couchbase Under the Hood : Couchbase is a modern distributed, multi model NoSQL database. Couchbase’s core architecture supports a flexible JSON data model at its foundation and uses familiar relational and multi model data access services to supply data to operational and analytic applications. Couchbase advantages include fast in-memory performance, easy scalability, mobile synchronization to, from, and among Couchbase Lite, always-on 24×365 availability, advanced security, and affordable cloud deployment alternatives. Couchbase can be accessed as a fully-managed database- as-a-service called Couchbase Capella, and also offers Kubernetes-managed containerized cluster deployments with its Cloud Native Database Automation product line.

Couchbase also supports local installations of its Community and Enterprise edition binary packages. As a multi model database, Couchbase supports multiple data access methods within a dynamic data containment structure, on top of a flexible JSON document data format. Couchbase consolidates multiple data access layers and engines into a single platform that would otherwise require single-purpose databases to work together. This “polyglot persistent” design architecture was introduced in the early 2000s so that RDBMS.

NoSQL databases could coexist in supplying data to applications. Couchbase provides the performance of a key-value powered caching layer, the flexibility of a JSON document-based dynamic source of truth, and the reliability of a relational database system of record. Couchbase eliminates the need to manage data models and consistency between multiple systems, learn different languages and APIs, and manage independent technologies. This paper describes how the internal components of the Couchbase database (Capella, Server, and Mobile) operate with one another. It assumes you have a basic understanding of Couchbase and are looking for a deeper technical understanding of how things operate beneath the surface.

Essential NoSQL requirements and features

NoSQL databases evolved beyond enterprise relational databases to address performance and flexibility deficiencies made evident as applications became more sophisticated and “Big Data” became an industry-standard buzzword. Relational databases tend to operate primarily as systems of record, maintaining transactional data in a highly consistent manner.

But several architectural principles (e.g. normalization of objects, adherence to fixed schema and data typing, single node transactional design, two-phase commit) have made them difficult to modify after deployment and scale to larger distributed workloads while simultaneously delivering responsive and highly available applications.

Pragmatic business needs for more advanced technical requirements have pushed multimodel NoSQL databases to the forefront. The business needs for high performance, application-driven flexibility over the makeup of its data, distributed processing and mobility, and the overarching need to lower operational costs andescape vendor lock-in are key drivers as to why organizations seek out cloud-native NoSQL systems. These modern requirements have driven Couchbase’s development from inception.

he original multi-model NoSQL database

The original multi-model NoSQL database Couchbase was originally founded through the merger of two open source database companies, CouchOne and Membase. CouchOne employed developers of Apache CouchDB, an original, highly-reliable, document database, while Membase employed developers of memcached, a highperformance, memory-first, key-value database.

The merger of these teams led to the design of Couchbase, a reliable, scalable, fast in-memory, key-value database with document-based access and storage. In this model, document identification “keys” store “value” data as a JSON document. Couchbase was the first of its kind, dual model access database, setting the standard for advancing consolidation of single-access NoSQL datastores. Couchbase further distanced itself from its origin sources by adding support for SQL++ (aka N1QL) as its primary query language.

Today, multimodel convergence continues to grow in order to address the variety of functional demands from modern applications. Unfortunately, many people still confuse Couchbase with CouchDB even though they have evolved along their own diverging paths, and no longer resemble each other whatsoever.

Couchbase favors and supports the open source development model. The source code to the Community Editions of the Couchbase database and its mobile product line is available for non-commercial use under the Business Software License (BSL 1.1), which converts to the permissive Apache 2.0 license after four years. Software development kits (SDK’s) for more than a dozen application and mobile programming languages are available as Apache 2.0 open source. Couchbase also maintains a robust library of open source projects at couchbaselabs.

These principles of speed, flexibility, familiarity, and affordability have been built in the very core of the database engine to ensure low latency and reliable, yet easy to manage, replication. Around this core are a set of data access services that run and scale independently of each other. These are delivered through a unified programming API, established security capabilities, and external technology integrations, and made available through fully managed and self-managed offerings including Couchbase Capella, a fully-hosed database-as-a-service, and through the Kubernetes-based, Cloud Native Database Automation product line for self-managed deployments.

JSON document data model

The JSON data model supports basic and complex data types: numbers, strings, nested objects, and arrays. JSON provides rapid serialization and deserialization, is native to JavaScript, and is the most common REST API data format. Consequently, JSON is extremely convenient for web application programming. Couchbase stores data as individual documents, comprised of a key and a value. When the value is JSON formatted, Couchbase provides rich access capabilities; when not, the document is stored as a binary BLOB and has more limited access characteristics.

A document often represents a single instance of an application object (or nested objects). It can also be considered analogous to a row in a relational table, with the document attributes acting similar to a column. Couchbase provides greater flexibility than the rigid schemas of relational databases, allowing JSON documents with varied schemas and nested structures. Developers may express many-to-many relationships without requiring a reference or junction table. Subcomponents of documents can be accessed and updated directly as well, and multiple document schemas can be aggregated together into a virtual table with a single query.

Buckets hold scopes, collections, and JSON documents—these are the primary organizing structures in Couchbase. Applications connect to a specific bucket that pertains to their application scope, applications query data by inquiring about documents within collections inside that scope. Memory quotas are managed on a per-bucket and per-service basis.

Security roles are applied to users with various bucket-level, scope-level, collection-level, and document-level constraints. In addition to standard Couchbase buckets, there are two specialized bucket types useful for different use cases. Ephemeral buckets do not persist data but allow highly consistent in-memory performance, without disk-based fluctuations.

This delivers faster node rebalances and restarts. Memcached buckets also do not persist data. It is a legacy bucket type designed to be used alongside other database platforms specifically for in-memory distributed caching. Memcached buckets lack most of the core benefits of Couchbase buckets including compression.

Couchbase nodes are physical or virtual machines that host single instances of Couchbase Server. Multiple instances of Couchbase Server cannot be installed on a node. A cluster consists of one or more nodes running Couchbase Server. Nodes can be added or removed from a cluster. Replication of data occurs between nodes and cross datacenter replication occurs between different clusters that are geographically distributed.

The core of Couchbase is the Data Service that feeds and supports all the other systems and data access methods. There are multiple services that offer different types of data access or processing including: Query, Indexing, Backup, Full Text Search, Analytics, and Eventing. A service is an isolated set of processes dedicated to particular tasks. For example, indexing, search, or querying are each managed as separate services. One or more services can be run on one or more nodesas needed.

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