List of Best and Most Popular NoSQL Database 2022

Data storage and retrieval are imperative for successful developmental processes, so developers employ the best NoSQL databases. 

Developers have for decades used SQL, which operates by linking multiple single tables to store information in databases. 

However, the flatter NoSQL databases replace traditional databases by unifying data storage in single, large tables.

The more diverse single-table data storage is typical of flat databases, of which NoSQL databases are part. Keep reading to find out more about the best NoSQL databases. 

Table of Content

1. What is NoSQL Database?
2. What are the Uses of NoSQL Databases?
3. Speed: When to Use a NoSQL Database
4. Available and Most Popular NoSQL Databases
   1. MongoDB
   2. Redis
   3. Cassandra
   4. HBase
   5. Neo4j
   6. Oracle 
   7. Amazon DynamoDB
   8. CouchDB
   9. Memcached
5. What is the Best Option
6. Conclusion

What is NoSQL Database?

To get you started on what a NoSQL Database is, you may need a little refresher on the meaning of a database.

A database is an assembly of information arranged to be easy to access, modify, and update. 

In that case, you must’ve used a database at least once while accessing online or offline products and services. NoSQL databases are also called non-SQL or “Not Only SQL” databases.

They are a deviation from the regular operation of traditional databases because they don’t support data storage in tabular relations, unlike conventional databases.

NoSQL databases are flexible because they don’t conform to a fixed schema. Schemas are descriptions of database structures, including names of tables, names of each table’s columns, the data types, and several other features of each column.

The description of a schema already shows you how complex it can be. So, not following a strict schema enables NoSQL databases to store and manage more significant volumes of data, whether unstructured, structured, or semi-, or partially structured.

The scalability of NoSQL databases has vast implications for developers as they can be more agile and efficient in their projects.

For instance, they can implement code changes faster than they could have with relational or traditional databases.

Think about the terabytes and petabytes of structured, unstructured, and hybrid data processing in the digital world.

These high-velocity data collections, generally known as Big Data, have grown so huge they can’t be efficiently managed or explored using traditional data management tools.

And, although NoSQL databases were initially aimed at modern web-scale databases, they are currently used extensively in real-time web applications and big data.

Huge amounts of data need capable databases to store and manage them. So, NoSQL databases help in easier and faster storage and retrieval of key-value, graph, document, and wide column data.

As a developer, it becomes easier with NoSQL to ditch the complex SQL operations. The reason is that NoSQL has a simple design and strong horizontal scaling capabilities.

That’s unlike RDBMS, where it’s difficult to achieve horizontal scaling to machine clusters. Relational Database Management Systems (RDBMS) store data in a tabular structure with rows to connect related pieces of data.

And as we pointed out earlier, the RDMS structure falls short in horizontal scaling. However, with NoSQL, it’s easy to scale real-world web and business applications horizontally.

MongoDB, Apache HBase, and Cassandra are among the most popular NoSQL databases available.

One of the best NoSQL database features is that they’re open-source, meaning they’re programmable or modifiable to meet desired enterprise specifications. Read on to see the uses of NoSQL databases.

What are the Uses of NoSQL Databases?

You can employ NoSQL database systems when you require any of the applications below:

Processing Large Amounts of Data

NoSQL databases generally outclass SQL databases when handling substantial amounts of data for a wide range of applications.

NoSQL databases are built to manage Big Data because of how seamlessly they enhance scalability. Besides, NoSQL databases are capable of handling web-scale applications with no need for complementing systems. 

Faster Development Pace

NoSQL comes to mind if you want to speed up your application development projects. In essence, the pace of development with SQL databases doesn’t come close to that of NoSQL databases.

Developers using NoSQL databases can implement rapid changes on datasets without adhering to a fixed data model. 

However, SQL databases will depend on DBAs to reorganize each table’s structure after implementing every change.

Updating data forms to ensure optimized storage structure and referential integrity takes a lot of time.

In other words, even if developers are completely in control of development databases as in SQL databases, they’d take a long time to update data forms. The results will include non-uniformity in data and development team conflicts.

Scalability and Accelerated Data Growth

NoSQL databases enable your applications to contain a high traffic influx while considerably reducing interruptions or lag times.

Through a scale-out strategy, the bulk of popular NoSQL databases make it very easy to scale traffic and ensure the smooth running of high-traffic systems. 

There are several perks to the scale-out strategy, such as enabling you to change the structure of your database or upgrade it to achieve zero downtime while enjoying significant volumes of traffic.

Scalability with NoSQL databases means the same database can handle all your analytical and transactional workload.

That’s to say, a single platform allows for horizontal scaling across different commodity servers.

In contrast, SQL databases function best with separate data warehouses and application databases.

The reason is to evade analytics with complex calculation queries, which hinders your production application’s performance. 

However, a blend of SQL will favor handling structured data or data subject to high normalization tendencies.

A relational database has the advantage of enforced structure over a NoSQL database.  The enforced structure ensures the sustenance of data relationships in the long run.

And, although SQL databases are popular for their improved application support and maturity level, NoSQL databases take the lead when it comes to scaling databases with rapid data growth.

In addition, NoSQL database protocols support the mixing of different types of NoSQL databases based on the needs of a specific application segment.

For instance, while some applications store most of their data in a document database such as MongoDB, they still utilize a graph database that captures connections between products or people.

Managing Varieties of Data

NoSQL databases make it easy for developers to manage and efficiently improve the structure of different data forms.

They are designed to store, model, and manage structured, semi-structured, and unstructured data all in the same database more efficiently.

That means NoSQL databases save you the time and resources of changing data to their code forms, i.e. you can store data just like you do your standard application tools. 

Speed: When to Use a NoSQL Database?

As we pointed out earlier, NoSQL databases don’t follow a fixed schema for data storage and retrieval, which is why they are said to be schemaless.

For that reason, NoSQL databases enhance the speed of development processes with improved write speed.

SQL databases require a validation process to ensure the data entered corresponds with the table’s schema.

As you saw earlier, this process is time-intensive since each data item must be validated against its unique column.

However, schemaless systems like NoSQL databases scrap this long, time-wasting process and save users quality time.

The NoSQL databases provide a better write throughput, i.e., write actions per second than SQL databases.

This advantage makes NoSQL databases the best fit for logging services that store and manage huge amounts of data.

Besides, NoSQL databases are the best fit for managing large series of unstructured and unrelated data types, unlike the highly structured SQL databases. 

Available and Most Popular NoSQL Databases

The following are some of the best NoSQL databases, a brief breakdown of each of them, and their respective advantages and disadvantages:

MongoDB

MongoDB, considered the most popular NoSQL database, is a document-oriented open-source database.

It is an accessible and scalable database available in C++ and can double as a file system. In addition, it can serve as the query language.

The MongoDB database is well suited for horizontal scaling through a process known as sharding involving data distribution in ‘shards’ across various machines.

Sharding helps to enable horizontal scaling, thus increasing throughput by decentralizing data storage and processing. MongoDB finds widespread application in well-known Javascript frameworks.

Because of the distributed nature of the database, the database never blanks out completely when a shard or set of logical data units becomes unavailable.

In such a case, the database remains partially active for reads and writes from the other shards.

Advantages of MongoDB

• It is a high-speed database
• It does not follow a fixed schema
• Horizontally scalable database
• Simple to set up
• High performance 
• Ad Hoc query supported
• Professional support from MongoDB Inc. to all its users

Disadvantages of MongoDB

• Uneconomical use of memory
• Large data size
• Has no support for joins
• Limited document nesting

Redis

Redis, the acronym for Remote Dictionary Server, is one of the most popular key-value stores, little wonder it’s called the “world’s most loved” database.

Although it is composed in C, Redis supports some Python, C++, PHP, Ruby, Perl, Scala, etc.

It can be described as an in-memory and persistent on-disk database, meaning that it stores all its data in RAM for backup using a disk.

Another interesting thing about Redis is its ability to process way over 250 million keys at a go. 

Also, Redis Enterprise, the richest version of Redis, provides top-notch performance, innovation, cost-effectiveness, and scalability on-premises, across clouds and hybrid deployments.

Redis Enterprise is used by some of today’s biggest organizations, including Microsoft, Dell, Mastercard, T-Mobile, FedEx, etc.

Advantages of Redis

• Easy to install
• Fast performance
• Supports a wide variety of data types
• Multiple utility tools serving for various use cases
• Replication feature in a distributed system

Disadvantages of Redis

• Requires knowledge of Lau in stored procedures
• Requires dataset to overlap comfortably in memory
• No support for joins

Cassandra

Developed by Facebook, Cassandra was designed to enhance inbox search. Being a distributed database, it is suitable for handling significant amounts of structured data.

Data stored by Cassandra are dispersed across multiple commodity servers, and you can conveniently scale up the data storage capacity of your online data service. 

With similar nodes in a cluster, there are no complex configurations to handle. Cassandra is an open-source database with code written in Java, plus CQL; the Cassandra Query Language resembles SQL.

For that reason, Cassandra is one of the top open-source databases available and used by some of the big fish like Facebook, Twitter, eBay, Cisco, Netflix, etc.

Because of its enterprise-grade features, Cassandra is a favorite among its related NoSQL databases.

These enterprise features enhance high data scalability and availability, enabling Cassandra to handle substantial amounts and provide almost real-time data analysis.

Again, Cassandra provides both synchronous and asynchronous replication per update, and since it offers high durability, it is great for applications that should always be on. And this is why it’s on of the top nosql databases.

Advantages of Cassadra

• No single failure point
• A highly scalable database
• A better choice for multi-data-center deployment, as well as disaster, failover, and redundancy recovery
• Seamless integration with other JVM-based applications
• Supports multiple DC replication

Disadvantages of Cassandra

• No support for ad hoc query
• Performance is unpredictable
• Inadequate support for aggregations
• Risk of inconsistent replicas

HBase 

HBase is a non-relational and distributed database created by Apache Software Foundation for Google’s BigTable database. 

The non-relational, column-oriented database seeks to support billions of rows by millions of columns of data. It runs on an HDFS (Hadoop Distributed File System) and allows you to enter servers anytime to enhance capacity.

It offers a fault-tolerant system for storing scanty data sets commonly encountered in big data. 

Additionally, it is an excellent fit for random read/write access to huge data volumes or real-time data processing.

The presence of multiple master nodes also ensures high data availability. HBase complements an easy-to-implement API for customer access.

It is composed in Java 8 and designed for linear scaling. Like traditional databases, it comprises a series of standard tables, having rows and columns. 

Each table compulsorily has a primary key element, which must be used in all attempts to access HBase tables.

One of its components, Avro, supports a series of primitive data types like binary data, numeric data, strings, etc.

Avro also supports a range of complex data types, including maps, arrays, records, and enumerations, plus the data can have a defined sort order. 

HBase integrates well with a big data, batch-processing query engine―Hive, to run fault-tolerant big data systems. It also depends on Zookeeper―built into its system―for high-performance coordination.

However, running a production cluster may require you to integrate your Zookeeper and HBase clusters.

Advantages of HBase

• Simple Java API for customers
• High-speed database
• HDFS file storage enables the handling of Big datasets 
• Enhances fast lookups for bigger tables
• Supports auto-sharding
• Offers quick lookups for larger tables
• Provides flexibility with schema design
• Access to unit rows form billions of records
• A license-free database

Disadvantages of HBase

• Absence of built-in authentications or permissions
• No transaction support
• No SQL structure support
• It may present memory problems in the cluster
• Only On-key indexing and support
• Has a single point of failure when using a single HMaster

Neo4j

Neo4j or the ‘native graph database’ executes the property graph model up effectively up to the storage level.

In other words, your data is stored just the way you whiteboard it, plus the database navigates and traverses the graph with pointers. 

Designed by Neo technology, the Neo4j database has Enterprise and Community editions.

The Enterprise edition offers everything included in the Community edition with additional enterprise features like backups, failover, and clustering functionalities. 

Advantages of Neo4j

• Provides high availability for big enterprise real-time applications
• Neo4j CQL query language commands are easy to learn
• It doesn’t need complex joins for data retrieval
• Simple tuning
• Easy retrieval of its adjacent node without indexes or joins
• Easy representation of semi-structured data

Disadvantages of Neo4j

• No support for sharding

Oracle 

Oracle DB, or Oracle RDBMS, was initially released by Oracle Corporation in 1979; however, Oracle’s stable (tested and verified version) release was in 2019.

It is one of the most trusted and popular database engines for storing, managing and retrieving data by type while maintaining the connections between the different data types. 

Oracle is a completely scalable relational database that global businesses use to process and manage data across wide and local area networks. 

The Oracle database has a network feature that allows cross-network communication. Without any bias, it is one of the best NoSQL databases among RDBM systems as it has one of the largest market shares.

It is no surprise that Oracle DB is a close competitor to Microsoft’s SQL Server in the enterprise database market. 

Again, Oracle DB is similar in structure to SQL server, which presents a great advantage to database administration learners.

Oracle database operates an inclusive system that supports major platforms like Windows, Linux, UNIX, and macOS. It offers various software versions based on budgets and requirements.

The Enterprise edition is the most robust and offers all the features, including optimized security and performance.

The Personal Edition comes close to the enterprise edition but lacks the Oracle Real Application Clusters feature.

Similarly, the Standard edition has conventional features for users who don’t need the optimized Enterprise edition features.

The Express Edition is the lightweight free and limited edition for Windows and Linux, while Oracle Lite serves mobile users.

Advantages of Oracle DB

• Various methods for cold, hot, and incremental backup and recovery, such as the robust Recovery Manager tool (RMAN)
• Efficient memory caching
• High-performance partitioning for splitting larger data tables into multiple pieces
• Problem-solving through peer to peer communities
• Highly secure and protects users’ data beyond compromise through prompt updates

Disadvantages of Oracle DB

• It uses up a  lot of storage space
• Costly for small institutions
• Hardware upgrades could require implementing Oracle.
• Its installation is resource-intensive

Amazon DynamoDB

Developed by Amazon.com, DynamoDB runs a non-relational database model, which enables it to include graphs, documents, and columnar data models in its system.

DynamoDB executes each of its queries by a user-identified primary key for the unique identification of each item.

DynamoDB also saves customers the stress of handling and scaling distributed databases.

For that reason, Amazon manages the setup, hardware provisioning, configuration, cluster scaling, software patching, and replication of the DynamoDB system.

Advantages of DyNamoDB

• Auto-scaling capability
• Easy to set up
• AWS identity ensures DynamoDB security
• At-rest encryption
• Minimizes management complexity for scaling and high availability during the highest usage or traffic periods. 

Disadvantages of DynamoDB

• Limited data size
• Paid table backups

CouchDB

CouchDB is an easy-to-use, web-oriented document storage database. Unlike some of the top NoSQL databases, it is not open-source.

Its flexible data model offers consistently high performance and easy scaling. The Couchbase Server is called JSON, and Couchbase uses JSON documents for representing application objects and their relationships.

Advantages of CouchDB

• Reduces network, storage, and memory costs
• The supportive admin panel gives you a good insight into the performance of your cluster.
• Provides aggregate optimization

Disadvantages of CouchDB

• Not an open-source database

Memcached 

As its name implies, Memcached is a high-performance, distributed, and open-source memory caching system designed to minimize database load, speeding up dynamic web applications. 

It is a dictionary of objects, strings, etc., in the memory, resulting from page rendering, API calls, or database calls.

Some popular companies like YouTube, Facebook, Wikipedia, Netlog, Twitter, etc., use the Memcached database in their systems. 

Advantages of MemCached

• Quick installation
• Extensive documentation with a large community

Disadvantages of MemCached

• No support for data redundancy
• Compatible only with Linux and BSD-similar systems
• Offers no support for read-through, CAS, and locks

What is the Best Option?

It’s not easy to decide which is the best NoSQL database because each has unique features and specialties.

And, although some of them may have more widespread applications, we can’t categorically call them the best because it depends on what you want to achieve with a database.

For instance, while Redis may be excellent with high-speed access to large data clusters, HBase is best for insanely large data sets with predictable data patterns to enhance aggregation and analytics.

And, even though MongoDB thrives at supporting complex queries and speeding up retrieval of individual documents, Neo4J excels at simple queries.

So, you see that they differ in the features they bring to the table and the issues they help resolve.

However, before selecting a NoSQL database, you may want to integrate a database performance monitoring tool like SolarWinds DPM for tracking and optimizing database performance.

Above all, check for the availability of managed DBaaS (Database-as-a-Service) services where the cloud provider can help you manage and maintain your database.  

Conclusion

Although traditional schema-adhering SQL databases present their unique perks, most of them consume a lot of time verifying data upon table columns to conform to schemas.

That’s the frustration that necessitated these most popular NoSQL databases we discussed above.

The best NoSQL databases are taking substantial portions in the database market, and we expect a more glorious future for NoSQL databases.

Now, we’ve covered top nosql databases and how they compare. Feel free to leave us a message if you have any further questions.