Traditional databases store data in structured tables, whereas NoSQL (non-SQL) databases use more flexible, non-tabular storage methods. NoSQL databases can store a wider range of data types, including document stores, wide columns, key-value stores, and graphs. These databases first emerged in the late 2000s to support massive horizontal scaling and high-throughput workloads for web applications. However, they have evolved to support many other applications, from real-time web applications to big data management.
Because NoSQL databases allow dynamic or schema-on-read models, they can handle unstructured, semi-structured, and structured data without costly migrations. This agility lets teams evolve data models and deploy application changes faster than with fixed-schema relational systems.
MongoDB, Apache Cassandra, Redis, Couchbase, and Neo4j are five of the most popular NoSQL databases currently on the market. This guide will serve as a NoSQL database comparison, helping you determine the best database for your business.
This NoSQL database list discusses the main differences between these top databases, their advantages and disadvantages, and where they are used. We’ll also describe our top recommendation for monitoring your NoSQL database, SolarWinds Database Observability, to help ensure your database performs as it should.
Here’s what we’ll explore:
- An overview of NoSQL databases
- Common use cases of NoSQL databases
- Advantages and disadvantages of NoSQL databases
- NoSQL database list
- The importance of NoSQL database monitoring
- The right NoSQL database to choose
An Overview of NoSQL Databases
A NoSQL database is designed to handle multiple data models, including key-value, document, column-family, and graph formats. These databases offer users flexibility when it comes to handling unstructured or semi-structured data, making them ideal for modern applications dealing with large volumes of rapidly changing data. Unlike traditional relational databases that store data in tabular forms with predefined schemas, NoSQL databases allow for dynamic schemas and horizontal scaling to ensure high database availability.
When comparing NoSQL and SQL databases, NoSQL databases offer more agility and scalability, making them better suited for real-time, big data, and cloud-based applications. However, SQL databases also have plenty to offer. The choice between NoSQL and SQL databases depends on factors such as transaction consistency needs, data complexity, and application scale.
Common Use Cases of NoSQL Databases
As stated above, NoSQL is a non-relational database management system (DBMS) that doesn’t require a fixed schema. Most NoSQL systems avoid server-side joins to maintain predictable performance at scale. Some, such as MongoDB’s $lookup and Cassandra’s materialized views, offer limited join-style operations, but developers often denormalize data or use application-level joins instead. NoSQL databases are commonly used in distributed data stores with large storage needs. Companies such as Facebook, Google, and X use NoSQL for their big data and real-time web applications, collecting terabytes of user data every day.
Advantages of NoSQL Databases
There are many advantages associated with using NoSQL databases, including:
- Elastic scalability: Designed to be used with low-cost commodity hardware
- Support for big data applications: Handles massive volumes of data
- Dynamic schemas: Accommodate data structure changes without strict rules
- Compatibility with inexpensive hardware clusters: Processes and stores more data at a lower cost
- Support for auto-sharding: Natively and automatically spreads data across an arbitrary number of servers without needing the application to be aware of the server pool composition
Disadvantages of NoSQL Databases
There are a few disadvantages to NoSQL databases:
- Many NoSQL databases trade off full ACID (atomicity, consistency, isolation, and durability) compliance for performance, though some have evolved to support ACID transactions in certain use cases. For example, MongoDB (since version 4.0), Neo4j, and Couchbase now offer multi-document or transactional ACID properties to varying extents
- Although NoSQL systems don’t use traditional SQL, many have their own specialized query languages. Some offer SQL-like interfaces, such as Cassandra Query Language (CQL), which provides a familiar experience for developers
- NoSQL databases are newer compared to relational databases, which means some may offer fewer mature features or have less stability in certain enterprise use cases
NoSQL Database List
There are plenty of NoSQL databases on the market today, but not all are the same. Each offers unique features, scalability options, and suitability for different applications. Some are optimized for read-heavy workloads, while others excel in write-heavy environments.
Although older NoSQL solutions were often limited to on-premises deployments, many modern NoSQL solutions are designed to take advantage of cloud and hybrid deployments. These allow businesses to scale better while providing high levels of availability and flexibility.
Some of the best and most popular NoSQL database options available include:
1. MongoDB
MongoDB is the leading document-oriented database. It was originally developed in 2007 to power high-scale web applications—later adopted by organizations such as DoubleClick—and overcome the rigid schemas and scaling limits of traditional relational DBMS. The enterprise version offers Kerberos, Lightweight Directory Access Protocol, auditing, and on-disk encryption features.
One of MongoDB’s major benefits is its flexible schema, which stores data as JavaScript Object Notation-like documents. As a result, it provides plenty of agility and flexibility for the type of records it can store, enabling fields to vary between documents.
MongoDB is a great option for high availability. It uses replica sets with data redundancy and automatic failover features, so your application can continue serving despite a failing node.
Since version 4.0, MongoDB has introduced support for multi-document ACID transactions, allowing developers to execute complex transactions with the same reliability guarantees found in relational databases.
As for the disadvantages of MongoDB, the management operations, including patching, are manual and time-consuming processes unless you choose one of the databases as a service option. Additionally, MongoDB suffers from memory hot issues at scale, where frequently accessed data exceeds available RAM, leading to increased disk I/O and slower queries. Mitigating this often requires indexing optimizations, more memory, or sharding.
2. Apache Cassandra
Apache Cassandra is another NoSQL database example. Initially developed for Facebook Inbox search functionality, Cassandra has become one of the most popular wide-column store database systems on the market. It is a favorite among NoSQL database users, mostly for its enterprise-grade features. These capabilities increase availability and scalability, allowing Cassandra to handle massive amounts of data and deliver near real-time analysis. Cassandra is written in Java and offers asynchronous and synchronous replication for every update. Its high durability makes it a great option for applications that need to be always on.
While MongoDB distributes data using sharding, which enables horizontal scaling and load balancing, Cassandra uses a masterless ring architecture. This means all nodes in a cluster are treated equally, with most nodes capable of achieving quorum. Like a traditional relational database, Cassandra stores data in columns and rows. However, it can provide additional agility by allowing rows to have different columns and enabling users to change the format of columns.
Since CQL closely resembles SQL, it’s relatively easy for SQL users to learn. This makes data manipulation and retrieval more intuitive, helping developers transition seamlessly. Additionally, Cassandra supports tunable consistency levels, allowing users to balance performance with stronger consistency when needed. Cassandra also offers advanced anti-entropy repair processes for read and write operations, improving cluster reliability and availability.
However, Cassandra’s distributed architecture can lead to inconsistent replicas. When a node goes down, its coordinator node will attempt to preserve data in the form of hints. When the failed node is brought online, the coordinator delivers these hints to assist with the repair process. This can create a burden for the coordinator node and result in the loss of data replicas.
Although Cassandra manages well when the primary key is known, it may not cope if the key is unknown. This is because it must scan all the nodes in the cluster, leading to high read time penalties.
3. Redis
Redis (Remote Dictionary Server) is an in-memory key-value store designed for ultra-low latency. Despite its simple data model, it supports diverse structures (lists, sets, sorted sets, streams, HyperLogLog) and persistence via Redis Database Backup (RDB) snapshots or Append-Only File (AOF) logs. Data are stored in a key-value structure, where each unique key is associated with a single value, such as a number, string, Boolean, or complex object. These keys can be used to store or retrieve the associated value and are distributed in a flat keyspace. Generally, key-value stores are used for caching and session management, including shopping carts, user preferences, and user profiles.
Salvatore Sanfilippo originally developed Redis to scale his real-time web log analyzer startup. Thanks to its distributed design and ability to hold all data in memory, Redis can quickly perform read and write operations, thriving in situations that require a cache.
Redis not only supports basic data structures but also several kinds of abstract data structures, including strings, lists, maps, sets, sorted sets, streams, spatial indices, bitmaps, and HyperLogLogs. This extensive compatibility makes Redis a versatile option for a wide range of applications, ranging from real-time analytics to distributed messaging. Redis also offers added flexibility by not enforcing schemas or strict naming conventions for keys.
Since Redis is an in-memory database that stores all its data in RAM instead of on disk, it provides users with incredibly fast access to data. The main memory is much faster than disk storage, making Redis an excellent choice for organizations that need to support online gaming, e-commerce, real-time analytics, and high-performing, scalable applications. Redis is capable of handling millions of operations per second.
Still, there are a few drawbacks. As an in-memory database, Redis is more likely to lose data during a crash or shutdown since data does not automatically persist to disk. However, Redis provides persistence options to help mitigate this risk. Users can enable RDB snapshots, which periodically save data to disk, or AOF persistence, which logs every write operation to ensure more durable storage. Additionally, Redis supports replication, allowing data to be copied across multiple servers to enhance reliability and failover protection.
Today, Redis remains an open-source NoSQL database and often ranks as the most popular key-value database. Its speed and versatility help companies significantly improve application performance and responsiveness, leaving users to enjoy low latency.
The Importance of NoSQL Database Monitoring
Once you’ve chosen a NoSQL database, it’s important to consider implementing a database monitoring tool.
SolarWinds Database Observability is an excellent NoSQL database monitoring solution. It monitors and alerts users to database issues in real time and helps with triaging, remediation, and proactive issue prevention. It offers 24/7 real-time monitoring and historical insights so you can better understand your database performance.
You can set up custom alerts to minimize alert fatigue while ensuring you never miss a critical issue. It provides in-depth analysis to optimize indexing and speed up data retrieval. While our self-hosted solutions (Data Performance Analyzer and SQL Sentry) support relational databases, NoSQL monitoring is available exclusively in our software as a service offering (Database Observability), allowing you to choose the deployment model that best fits your organization’s needs.
Choosing the Right NoSQL Database
MongoDB, Apache Cassandra, Redis, and other NoSQL databases each have their own benefits and drawbacks. The right database for you depends on many factors, including your application’s data model, scalability requirements, and performance demands. By evaluating your specific use case, you can select the database that best aligns with your requirements. No matter which NoSQL database you choose or how you manage it, implementing a database performance monitoring tool is essential for tracking and optimizing performance. SolarWinds Database Observability is a powerful and scalable tool that can help keep your applications up and running, allowing you to provide customers with the best possible experience. Discover everything Database Observability has to offer your organization today.
