Skip to content
Noroff Case Studies

Couchbase Case Study

Author: Bekzat Bagdat <BekzatBagdat>

Introduction

Couchbase is a open source NoSql JSON document database platform, that offers high-performance, flexibility, scalability, and speed. It achieves its high performance by using in-memory caching, which allows it to be much faster than other known relational databases such as MySQL,and PostgreSQL. It also performs significantly faster than other NoSQL databases like MongoDB. Couchbase also uses N1QL which is a query language that is similar to SQL, which makes it easier for people who are already familiar with SQL, where as MongoDB uses its own unique query language called MongoDB query language (MQL).

Couchbase Logo

Brief History

  • 2009: NorthScale and CouchOne Inc was founded. CouchOne Inc developed and provided financial support for Apache CouchDB, a open source, document database.
  • 2010: NorthScale got $5 million in funding from Accel Partners and North Bridge Venture Partners, and a $10 million investment by Mayfield Fund, and later same year NorthScale was renamed to Membase.
  • 2011: Membase and CouchOne merged together and became CouchBase Inc. Goal with CouchBase Inc was to build NoSQL document-oriented database system, which is easily scalable, and high-performing.

Main Features

Couchbase is a powerful NoSQL database platform, offering its own unique advantages, and making database management as easy and cost-efficient as possible. Here is the main features of this database system:

  • SQL++: Use of SQL-like query language to work with JSON data. This shortens learning curve for developers already familiar with SQL, and let them use the flexibility and speed of JSON with along with their SQL-skills. SQL++ also includes JOIN operations, which is often not present in other NoSQL database systems.

  • Key-value: Saving data as items with unique key, and value. The value can be either binary or JSON, and will be identified by a unique key, this can be defined by the developer or application when the item is saved. This allows for as efficient as possible data-lookup.

  • In-cache Memory: The most used data and indexes are cached in-memory for faster reads, writes are also performed in-memory and can be replicated, presisted synchronously or asynchronously, which ensures consistency.

  • Full-text search: Use of Integrated JSON search, that gives the developers ability to perform powerful searches without the need for any third-party software. Developers/Users can find content in the database by criterias such as text, latitude, longitude, and vector embeddings. Text search indexes are predefined to make the search faster than traditional field-based database scans.

  • Real-time Analytics: Ablility to perform complex BI and fast, low latency analtytical queries on the data. Since modern adaptive applications require operational and transactional data to create streamlined experience, the apps needs to work in real-time. Couchbase solve this problem by converging operational data and real-time analytics in one platform.’

  • Eventing: Couchbase offers eventing service that offers capabilities such as real-time data mutation management, alert setting, and data change propagation without the need for third-party tool installment. This improves business workflows using an event-condition-action model, and reduces costs and technical barriers.

  • Cross Data Center Replication (XDCR): a feature of Couchbase that automaticlly replicates data across data center, cloud regions and cloud providers. This ensures data recovery in case of a disaster, allows data to be as close as possible to the user, improves the speed, performance, and ensures that the data keeps being available even if one of the centers is down.

Couchbase Services

  • Couchbase Capella: which is a fully managed cloud Database-as-a-Service.

  • Couchbase Server: which is a self-hosted database server which can be downloaded and installed in various operation systems such as Windows, Linux and Mac.

  • Couchbase Mobile: which run as a standalone embedded database on mobile, desktop, and edge devices.

  • Autonoumous Operator: which is used to run easily within Kubernetes, that provides a Couchbase specific API for managing database clusters.

Couchbase Applications in the Industry

  • E-Commerce: Couchbase’s high-performance, ensures that customers get fast, engaging, and reliable shopping experience .

  • Energy & Utilities: Couchbase is highly reliable and responsive even in remote locations with poor connectivity.

  • Financial Services: real-time risk management, enterprise-wide analytics, digital banking, and automated compliance.

  • Gaming: Couchbase can give millions of gamers reponsive and personalized experiences across different devices, by maintaining 100% uptime and scale in real time.

  • Media & Entertainment: Couchbase’s high performance and scalability, is perfect for use in this industry.

  • Government: Couchbase can be used to deliver public services using a single platform that connect citizens to their munipalities and governments.

  • Healthcare: Couchbase is highly scaleable, high-performant and reliable, which is crucial in this field.

  • High Tech: Couchbase can be used to build highly engaging, reponsive and scalable AI-powered applications.

  • Manufacturing & Logistics: Couchbase ensures that field employees get a reliable application that operates fast from anywhere, regardless of the network connectivity.

Strengths and Weaknesses

Strengths:

  • In-Memory Database (IMDB): Data is stored in the RAM, which speeds up data access and reduces proccessing times, which significantly reduces response latency. This also results in high scalability, making it easier to manage large data volumes.
  • Data Model: data model is based on JSON, which means its simple, lightweight, and readable. It supports data types like numbers, strings, embetted documents and arrays. It provides greater flexibility compared to other relational databases, by storing JSON documents with various schemas. It also allows to express many-to-many relationships without the need for a reference or junction table.
  • High-performance & scalability: Couchbase is high-performing and scalable, which is good for real-time applications

Weaknesses:

  • In-Memory Database (IMDB): First weaknesses of In-Memory Database is that RAM can become expensive compared to disk storage, especially when maintaining large amounts of data in memory. Another disadvantage of IMDBs is that if the power is lost, so is the data, but Couchbase provides replication and presistence mechanisms that will endsure that the data presists on disk or replicate over the network to prevent data loss. Also there is hardware limitations problem that limit how much individual system can have, but this can be overcomed by using horizzontal scaling that is provided by Couchbase DBaaS.
  • Steep Learning Curve: Couchbase’s advanced features and configuration options can be hard to learn for developers with little experience in NoSQL databases. -Limited SQL Support: CouchBase’s SQL-like query language (N1QL) does not provide same level of SQL support as traditional relational databases, this can be a challenge teams that are used to work with regular SQL.

Market Comparison (Couchbase and MongoDB)

Both Couchbase and MongoDB is NoSQL databases that has its own strengths and unique features. Here is a comparasion between these two:

Data Model

  • Couchbase: Flexible schema-less data model, documents are stored as key-value pairs, supports formats such as JSON, XML or binary.
  • MongoDB: Dynmaic schema, agile and flexible data models, BSON (Binary JSON) as default data storage format.

Scalability and Performance

  • Couchbase: Horizontal scalability, data distrubution across multiple nodes through its distributed architecture and automatic data sharding, ensuring high availability and fault tolarance. High-performance due to efficient data caching mechanism and a highly scalable data storage engine.
  • MongoDB: Horizontal scalability, data distrubution across multiple nodes, also supporting sharding, but needs manual configuration and management. Emphasizes on flexibility and developer productivity, by providing features such as rich secondary indexes and powerful aggregation pipelines for complex data manipulations.

Querying language and indexing capabilities

  • Couchbase: N1QL, a SQL-like query language on JSON documents, supports ad-hoc queries and joins, provides a flexible indexing mechanism to engance query performance.
  • MongoDB: MQL, MongoDB own query language designed to work with JSON documents. Provides rich sets of operators, functions, supports indexing, including single-field indexes, compound indexes, and text indexes.

Use Cases and Industry

  • Couchbase: Best used where high performance, scalability and low-latency data access is required. Couchbase is often used in real-time analytics content management systems, customer data platforms and application that demand fast response times. Used in industries such as gaming, e-commerce, and telecommunications.
  • MongoDB: Best used in cases where flexibility and scalability is required. MongoDB is document-oriented, which makes it a popular choice for content management systems, social networks, Internet of Things (IoT) platforms, for applications that need agile development and frequent schema changes. Used in industries such as finance, healthcare, and media.

Conclusion

Couchbase is a NoSQL database platform, that offers high-performance and scalability, and low-latency. It has in-memory caching, it uses SQL-like query language (N1QL) on JSON document which includes JOIN operations, which often not seen in other NoSQL databases. Couchbase suits for applications where real-time processings are important, like gaming, telecommunication and e-commerce. Downsides of Couchbase is steep learning curve, limited SQL support, and costs the In-memory Databases can bring.

References

Additional Resources