mongodb 7 challenges second level banner
See how MongoDB performs in the NoSQL technical comparison report

MongoDB is a popular NoSQL document database that many developers have played around with. It has some nice features, and can be a good fit for some use cases – typically small-scale applications running on a few nodes. But companies report problems when trying to scale MongoDB to support more users and bigger workloads on clusters with multiple nodes.

The Couchbase Data Platform delivers unparalleled performance at scale, while also providing the unmatched agility and manageability that today’s businesses require to continually improve their customer experiences. Couchbase's latest release is currently the best NoSQL database platform and introduces new features that makes building rich customer apps easier, including N1QL enhancements, multi-datacenter support in the SDK, N1QL query plan visualization tools, adaptive indexing, and a fully integrated full-text search capability. Learn what's new in Couchbase Server 5.0 in the latest whitepaper.

When comparing Couchbase vs. MongoDB, the former has an entirely different, in-memory architecture that’s purpose-built to deliver consistent high performance in distributed environments, at any scale. Couchbase’s revolutionary Multi-Dimensional Scaling (MDS) allows users to add nodes that expand specific services (data, indexing, and query) to accommodate different workload types and growth patterns. So, with Couchbase, you get both amazing performance at scale along with exceptional agility and ease of development and deployment.

Some of the world’s largest companies run their most demanding, mission-critical applications on Couchbase – including AT&T, Comcast, eBay, Gannett, GE, LinkedIn, Amadeus, Marriott, PayPal, Tesco, Verizon, VISA, Wells Fargo, and many others.

7 frequent challenges with MongoDB and how the Couchbase Data Platform avoids them

Challenge 1:

MongoDB is hard to scale from a single replica set to a fully sharded environment


Due to its master-slave architecture, MongoDB requires a complex process, with lots of moving parts and manual configuration, to scale from a single replica set to a fully sharded environment.


Couchbase has a modern, masterless, and elastic architecture with no single point of failure. Deploying and scaling Couchbase is a simple push-button process due to single-node type architecture.

Challenge 2:
Performance at scale

MongoDB’s performance rapidly degrades with increasing users


MongoDB’s architecture limits its ability to efficiently support many concurrent users with a single node. Beyond a few dozen concurrent users per node, performance rapidly degrades. So the only way to effectively deal with performance degradation is to add more hardware resources, which increases the cost and complexity of your deployment.


Couchbase’s memory-first, network-centric architecture is designed for predictable and consistent performance at any scale. Couchbase easily supports hundreds of concurrent users on a single node with little to no impact on performance. With its unique ability to scale horizontally across multiple nodes, Couchbase delivers the same performance to the first user as it does the millionth user.

Challenge 3:
Replication and failover

MongoDB is significantly susceptible to data loss and inconsistency


The way MongoDB handles replication and failover (by promoting “secondaries” to “primaries” automatically) can result in lost writes and inconsistent reads. So if a primary goes down, MongoDB is likely to suffer data loss or inconsistency. This risk is one reason why MongoDB deployments need to be closely monitored at all times.


Couchbase, which was purpose-built for distributed environments, has an entirely different approach to replication and failover that significantly reduces the potential of data loss and inconsistency. During a failover, Couchbase prevents two distinct nodes from accepting simultaneous reads or writes of the same data.

Challenge 4:

MongoDB requires a third-party cache to help it perform


Because MongoDB cannot handle many connections and many concurrent users per node, companies often need to add a dedicated third-party cache to help MongoDB meet their performance requirements. The need for a third-party cache can add both cost and complexity to a MongoDB deployment.


Couchbase has a fully integrated managed object cache that completely removes the need for a third-party cache. In fact, Couchbase leverages the memcached protocol, which is widely regarded as a de facto standard and the industry-leading high-performance cache.

Challenge 5:
Multi-datacenter deployment

When deployed in multiple geographies, MongoDB can’t perform all writes locally


Due to its master-slave architecture, and its use of “primaries” and “secondaries,” MongoDB cannot perform all writes locally when it’s deployed across multiple data centers in different geographies. This means it has to perform at least some writes to remote locations, which can increase latency and degrade application performance.


Couchbase’s masterless, distributed architecture, and its built-in support for cross datacenter replication (XDCR), means that all writes can be performed locally rather than to a remote location. This capability minimizes latency to help optimize application performance.

Challenge 6:

MongoDB lacks a mobile solution


MongoDB does not have a complete solution to support mobile applications. As a result, you have to write custom services for your mobile apps to access data in MongoDB. You either have to write your own code to synchronize data on the mobile device with data in a remote server, or forego synchronization and instead pull data from the remote server for every request. This means that your app always needs a reliable internet connection to work properly and may suffer performance problems due to network latency.


Couchbase provides a complete mobile solution – Couchbase Mobile – that includes an embedded JSON database (Couchbase Lite) and a pre-built synchronization solution (Sync Gateway). You can use Couchbase to easily build mobile apps that always work, with or without an internet connection.

Challenge 7:

MongoDB is time consuming to manage and maintain


Due to its master-slave architecture, the topology of a MongoDB deployment can be complex and increasingly complicated as you try to scale it. Deploying MongoDB requires lots of manual configurations and includes numerous components: routers, config servers, arbiters, primary instances, and secondary instances.


Couchbase’s masterless, distributed architecture is elegantly simple. Installing Couchbase and setting up a cluster is a fast and easy process, with minimal components and configuration requirements. A multi-node Couchbase cluster can be set up in minutes, and adding or removing nodes is a simple, push-button process.

Why enterprises choose Couchbase over MongoDB

directv logo

Today’s viewers demand seamless experiences and constant innovation. Finding MongoDB difficult to use and scale, DirectTV chose Couchbase for unparalleled performance at scale, bi-directional XDCR to keep services available for viewers 24/7, and N1QL for powerful queries.

Learn more
viber logo

Pushed to scale at a rate its MongoDB and Redis backend could no longer support, messaging platform Viber switched to Couchbase. Supporting close to a million operations per second, datasets with billions of records, and robust enough to avoid downtime, Couchbase helped Viber cut servers by more than 50%.

Learn more
nuance logo

Nuance, a speech-recognition and imaging software company, knew its monolithic, all-Oracle environment was expensive to scale and inflexible for varied data types. As it explored NoSQL, it found MongoDB hard to manage. It chose Couchbase for easy, cost-effective performance at scale and bi-directional replication.

Learn more
staples logo

Staples needed to better manage B2B catalogs using 1.6 billion rules applied in real time. While it explored MongoDB, an inability to scale easily and affordably led to canceled projects. Couchbase not only enabled Staples to simplify its catalog management using N1QL and JSON, but also increased their database performance and reliability.

Learn more

Talk to a Couchbase Solutions Engineer