Skip to main content

Best NoSQL Databases Shortlist

Below is my recommended list of NoSQL databases, along with a summary of what they do best:

  1. MongoDB – Best document-based NoSQL database
  2. Redis – Best key-value NoSQL database
  3. OrientDB – Best multi-model NoSQL database
  4. Cassandra – Best wide-column NoSQL database
  5. Couchbase Capella – Best for SQL-like functionality
  6. Neo4j – Best graph-based NoSQL database
  7. Elasticsearch – Best document-based NoSQL database for integration
  8. HBase – Best column database for managing large data
  9. Oracle Coherence – Best cloud- and grid-based NoSQL database
  10. Amazon DynamoDB – Best NoSQL database for user-friendliness
  11. IBM Cloudant – Best NoSQL database for schema-less document storage
  12. RavenDB – Best NoSQL database for fully-functional ACID transactions

As the volume and complexity of big data have grown, so too have the capabilities of NoSQL databases. Businesses are turning to new, more sophisticated database solutions to solve emerging big data problems.

This article will help you select the best options available to you today, by considering each tool's unique strengths and answers to common questions.

What Are NoSQL Databases?

No Structured Query Language (SQL) databases are non-relational databases. Unlike traditional relational databases, as they capture and process data without defined tables and columns. This allows them to store large volumes of structured and unstructured data from multiple sources.

The four most frequently used NoSQL databases are document databases, graph databases, key-value databases, and wide-column databases. Each type of database has its unique advantages and use cases, as I discuss below.

Overview of the 12 Best NoSQL Databases

Here are my recommendations of the 12 best NoSQL databases and the scenarios where I think each one performs best.

1. MongoDB - Best document-based NoSQL database

MongoDB Atlas NoSQL database
Use MongoDB to import CSV and JSON files and design your data schema. (Source)

MongoDB is an open-source, document-based database. It can store structured data in the popular JavaScript Object Notation (JSON) format or in a proprietary format called Binary JSON (BSON). BSON can store more data types than JSON, and it can encode the type and length of a piece of information, making it easier for a machine to parse (convert formatted text into a specific data structure).

Why I Picked MongoDB

I chose MongoDB because it excels at what document databases do best: providing flexible data models that can evolve as your application needs grow. Since MongoDB scales horizontally, you can quickly add new servers to accommodate larger amounts of data clusters, and it works well for applications that require high performance.

MongoDB Standout Features and Integrations:

Features that make MongoDB stand out include sharding and replication. Sharding splits up larger datasets into smaller chunks, then shares those chunks with other machines, spreading the workload. The replication feature lets you provide data redundancy across multiple servers, minimizing server disruption.

Integrations: Although you can integrate third-party APIs into MongoDB, there are also partner integrations that are specific to MongoDB, such as Vercel, Netlify, SAML SSO Providers, HashiCorp Terraform, and HashiCorp Fault.

Pricing: Dedicated from $57/month or serverless from $0.10/million reads

Trial: Free version available


  • BSON widens data type support while reducing parsing
  • Comprehensive documentation and large community support
  • No predetermined schema improves flexibility and scalability


  • BSON uses up more storage space than JSON
  • Some performance issues with larger databases

2. Redis - Best key-value NoSQL database

Redis database on MacOSX
Redis is a key-value database used for real-time applications like caching and queuing. (Source)

Redis is an open-source, in-memory, key-value database. It delivers sub-millisecond response times, which makes it ideal for all kinds of real-time applications, such as updating the leaderboard in an online multiplayer video game or providing real-time shipping information to a customer awaiting a delivery.

Why I Picked Redis

I was impressed by Redis’ fast performance. It stores data in memory instead of on a physical disk or Solid-State Drive (SSD), so when you request data, there is no need for it to pass through the disk, making it more efficient than many competitors.

Redis Standout Features and Integrations

Features that stood out to me include the automatic failover. When the master database doesn’t perform as expected, Redis promotes a replica of that database to master status, which minimizes server downtime by automatically switching operations between servers.

Integrations: Redis integrates with native modules to enhance the platform’s capabilities. Some of the most popular integrations include RediSearch, RedisJSON, RedisGraph, RedisBloom, redis-cell, RedisTimeSeries, and RedisAI.

Pricing: From $7/month or $0.881/hour

Trial: Free version available


  • In-memory data storage delivers fast performance
  • Useful for real-time applications such as gaming leaderboards and analytics
  • Automatic failover guarantees high availability


  • No Graphical User Interface (GUI)
  • Lack of documentation

3. OrientDB – Best multi-model NoSQL database

OrientDB multi-model database
The OrientDB interface lets you execute queries to gain insights quickly. (Source)

OrientDB is an open-source, multi-model database. It supports all types of NoSQL database, including graph, key-value, object, and document models. So your business can build and manage multiple NoSQL databases on one system, with no need to invest in multiple products.

Why I Picked OrientDB

I chose OrientDB because its engine is built from the ground up to natively support the full functionality of each NoSQL database type. I found this to be a better approach than merely replicating the interfaces of other models, which achieves limited speed and scalability.

OrientDB Standout Features and Integrations:

Features that make OrientDB great are the multi-master architecture and Java support. The multi-master distributed architecture lets you distribute multiple databases across multiple servers and then configure those servers individually. Also, since OrientDB is written entirely in Java, I found it easy to run on different platforms without manual installation.

Integrations: OrientDB has its own Java Database Connectivity (JDBC) drivers, which lets you integrate many pre-built tools into the platform. Some of the most popular native integrations are Teleporter, Orient DBL, Spark Connector, and Neo4j Importer.

Pricing: Enterprise edition from $5,970

Trial: Free version available


  • Native support Graph, Key-Value, Document, and Object databases
  • Easy to setup and use
  • Free community edition is great for small businesses


  • High upfront cost for Enterprise edition
  • Small community and limited documentation

4. Cassandra – Best wide-column NoSQL database

Apache Cassandra enterprise database
Cassandra stores data in columns, so you can easily load up an entire column and search for a specific query. (Source)

Apache Cassandra is an open-source, wide-column database that supports hybrid cloud and on-premises database replicating and audit logging. Because the platform is freely available and used by thousands of companies, I think it is a great solution for businesses that want to manage large active data sets at low cost.

Why I Picked Apache Cassandra

Cassandra stands out to me as a powerful wide-column database with lots of scalability. You can simply add more servers horizontally to the cluster as your data needs get bigger. Also, Cassandra uses a column-family data model, so it’s accessible to traditional relational database users.

Cassandra Standout Features and Integrations:

Features that impressed me were its ability to support high workloads and maintain data consistency. Cassandra has been tested on large clusters of up to 1,000 nodes, with better performance than similar platforms like MongoDB. I also like the hinted handoff feature, which corrects for missed data writes if a replica node is unavailable to accept a change. This maintains data consistency across multiple servers.

Integrations include a variety of pre-built connectors, such as New Relic, IRI Voracity, DbVisualizer, Sematext Cloud, Flex83, Retool, and DbSchema. You can connect Cassandra to Google Cloud through the Datastax Astra DB platform, which I found to help streamline Cassandra's steep learning curve with user-friendly development tools.

Pricing: No paid plan

Trial:Free version available


  • Support for hybrid cloud (private and public) and on-premises
  • Can handle large volumes of unstructured data
  • Horizontal scaling to accommodate growing data needs


  • No ad-hoc queries
  • Requires periodic manual maintenance

5. Couchbase Capella – Best for SQL-like functionality

Dashboard for Couchbase Capella
Couchbase Capella lets you create, edit, run, and save SQL++ queries, import data, and securely connect applications. (Source)

Couchbase Capella is a cloud database platform, combining the speed and flexibility of a NoSQL database with the benefits of an SQL database. It also has an app development solution called Capella App Services, which you can use to design and deploy IoT, mobile, and edge applications.

Why I Picked Couchbase Capella

I chose Couchbase Capella because it is accessible to those who are familiar with SQL databases. It uses the SQL++ query language for operations and analytics. I like how this streamlines the move from traditional relational databases to non-relational databases, with familiar features like ACID transactions and hierarchical schemas.

Couchbase Capella Standout Features and Integrations:

Features that make Couchbase Capella stand out include the Couchbase Playground, which lets you run snippets of code across multiple languages in a secure sandbox. This gave me a better idea of what Capella could do without the free trial period. Also, Capella App Services is easy to use, with preset backend infrastructure to fast-track the development process.

Integrations include native support for Confluent Cloud, Workato, and Microsoft Azure.

Pricing: From $0.28/hr per node

Trial: Free trial period available


  • Combines the benefits of SQL and NoSQL databases in one platform
  • Built-in app development and deployment service
  • Great value for money


  • Steep learning curve
  • Limited integrations

6. Neo4j – Best graph-based NoSQL database

Neo4j visual user interface
Here’s an example of Neo4j’s graph database user interface. (Source)

Neo4j is a graph-based NoSQL database used to develop applications, create and deploy Artificial Intelligence (AI) and Machine Learning (ML) pipelines, and perform detailed analytics. It is particularly suited to data scientists, application developers, and similar enterprises. With the intuitive graph-based user interface, establishing patterns and relationships with large amounts of data is easy.

Why I Picked Neo4j

Neo4j grabbed my interest because of its clear user interface and advanced graphing capabilities. I found it was helpful for uncovering hidden insights in complex data relationships, where trends and patterns may not be obvious right away. I was also impressed by how easily the platform scales horizontally. This is thanks to Autonomous Clustering, which automatically copies your datasets to the most optimal servers based on your rules and guidelines.

Neo4j Standout Features and Integrations:

Features that I like in Neo4j are the advanced analytics and ML solutions. The platform offers a range of visualizations, graph algorithms, and ML models, which you can use to create network maps and identify relationships between different objects.

Integrations include a range of native universal connectors, such as Apache Spark, Kafka Connect, and the Neo4j Data Warehouse connector.

Pricing: Pricing upon request

Trial: Free version available


  • ACID transactions ensure database operations happen across all nodes
  • Strong community and documentation
  • Surprisingly easy to learn and use


  • Custom pricing for Enterprise edition
  • New versions can introduce new errors

7. Elasticsearch – Best search-based document database

Snippets of Elasticsearch dashboard
Elasticsearch is a unique platform that incorporates search into the practice of database management. (Source)

Elasticsearch is a distributed database that has a uniquely fast search function. Based on the Apache Lucene library, you can use Elasticsearch across a range of industries to improve the customer experience, streamline the DevOps lifecycle, and gain insights into production environments.

Why I Picked Elasticsearch

I chose Elasticsearch because it’s a powerhouse for searching data. Aside from being able to store and analyze large amounts of data in real-time, Elasticsearch can provide answers in milliseconds. It achieves this speed by converting unstructured data into specially configured documents optimized for language-based searches. This allows users to find the information they need quickly and easily.

Elasticsearch Standout Features and Integrations:

Features that I like about Elasticsearch include the advanced analytics, which help you fine-tune search results to improve the experience. The ML capabilities are also very powerful, and can personalize search experience based on a user’s location, purchase history, and customer account.

Integrations with Elasticsearch are a strong point. Some of the best pre-built integrations include 1password, Amazon CloudWatch, AWS ECS, Graphite, HA-Proxy, and LastPass.

Pricing: From $95/month

Trial: Free trial available


  • Unique search capabilities
  • Huge range of integrations
  • Affordable basic plan


  • Concept can be confusing at first
  • Lack of security features

8. HBase – Best column-oriented database for storing very large datasets

HBase web app dashboard
With the HBase dashboard, you can monitor servers, backup masters, and tables. (Source)

HBase is a column-oriented, NoSQL database that runs on the Hadoop Distributed File System (HDFS). This means the HBase platform is particularly good at managing large data, as the system is almost entirely fault-tolerant.

Why I Picked HBase

HBase stood out to me because it is extremely good with large datasets. It can scale across thousands of servers and can accommodate data up to terabytes in size. I also appreciated that HBases uses HDFS to detect faults across all servers and automatically recover quickly. It excelled at minimizing server downtime for large systems.

HBase Standout Features and Integrations:

Features that I like are its scalability and integrations. Since HBase stores data like a relational database in columns and rows, this makes it easy to scale horizontally across multiple servers. I found it incredibly easy to use HBase with other platforms like Apache Hadoop.

Integrations include Hive, a database solution used to analyze time-sensitive data in the same Hadoop cluster. Hbase can leverage Hive's analytical abilities, while Hive can leverage Hbase's real-time querying abilities.

Pricing: No paid option

Trial: Free version available


  • Free to use
  • Integration with Apache Hadoop
  • Horizontally scalable across thousands of servers


  • Fewer built-in features than Cassandra – relies on third-party integration
  • CPU and memory intensive

9. Oracle Coherence – Best cloud- and grid-based NoSQL database

Oracle Coherence main dashboard
Gain fast access to key-value data with Oracle Coherence’s in-memory data grid. (Source)

Oracle Coherence is an in-memory, key-value database that delivers strong scalability and performance for enterprise applications. Using low-latency data storage to read, write, and query latencies allows businesses — running multiple applications in different languages — to quickly maintain data consistency in real-time.

Why I Picked Oracle Coherence

What I love about Oracle Coherence is its support for asynchronous event streaming. This means you can incorporate event models into your event-driven architecture, allowing for efficient communication between microservices like servers and clients.

Oracle Coherence Standout Features and Integrations:

Features that really shine in Oracle Coherence are the data source integration and multi-site data federation. Data source integration helps keep the data you are working on up to date by replicating any changes you make to a HotCache, and multi-site data federation helps keep your cached data synchronized with all your clusters.

Integrations for Oracle Coherence include Spring, which enables you to configure the Coherence cache for applications running on Spring. Coherence also has native support for Oracle WebLogic Server and Oracle NoSQL database.

Pricing: Fixed license from $15,456/year

Trial: Free version available


  • Free to use
  • Many features to maintain data consistency
  • Strong community support and documentation


  • Limited default security
  • Difficult upgrade process

10. Amazon DynamoDB – Best NoSQL database for user-friendliness

Amaxon DynamoDB table dashboard
With Amazon DynamoDB, you can create and manage multiple tables from a single dashboard. (Source)

Amazon DynamoDB is a NoSQL database that supports both document and key-value data models. It is a cloud-based service that lets you store items, tables, and attributes. You can use the service on pay-as-you-go or provisioned pricing model, whichever suits your workload.

Why I Picked Amazon DynamoDB

Aside from being a fully managed NoSQL database with high availability and durability, what I like the most about Amazon DynamoDB is its Amazon Web Services (AWS) integration. This helps you do more with your data, for example, by letting you import and export from your S3 buckets. I also appreciated the ease of use, thanks to excellent documentation and a user interface that is clean and intuitive.

Amazon DynamoDB Standout Features and Integrations:

Features that I like include the DynamoDB Accelerator (DAX), an in-memory cache that lets you process millions of requests per second. This minimizes the time your database spends on each query. I also found DynamoDB much easier to set up compared to MongoDB, as the AWS cloud is easier to navigate.

Integrations are native with other AWS services. From Amazon S3 to Cognito and Redshift, there is a lot you can add to make DynamoDB better, such as automation for repetitive tasks and managing SQL databases in the same dashboard.

Pricing: Write operations from $1.25/million requests; read operations from $0.25/million requests.

Trial: Free version available


  • Easy to set up and use
  • Strong documentation and support
  • AWS integration to extend functionality


  • No on-premises option
  • Limited to AWS cloud

11. IBM Cloudant – Best serverless NoSQL database

The IBM MyCloudant portal
The IBM Cloudant dashboard lets you create and manage databases, manage replication, and monitor active tasks. (Source)

IBM Cloud is a fully managed, distributed database that runs on a serverless schematic, meaning you don’t have to manage server configuration and scaling. This lets you build and run databases without worrying about the backend.

Why I Picked IBM Cloudant

I picked IBM Cloudant because it’s serverless and incredibly secure. You only pay for the resources you use, and you can scale up or down as your data needs change. For security, I was impressed by IBM Key Protect, which gave me total control and visibility over encrypted keys.

IBM Cloudant Standout Features and Integrations:

Features that I liked include the powerful API, which lets you store JSON documents using an HTTP API. Although MongoDB and Couchbase Capella can do the same, neither match the sophisticated security of IBM Cloudant.

Integrations that are possible with IBM Cloudant include IBM App Connect, which helps you connect all of your applications and data in any environment. Cloudant natively integrates with IBM Cloud Log Analysis, so you can analyze logged information such as the number of page views for a web application.

Pricing: From $1/month

Trial: Free tier available


  • Comprehensive security
  • Serverless schema for easy configuration
  • Free version available


  • Some documentation is out of date
  • Slow time to index large databases

12. RavenDB – Best NoSQL database for fully-functional ACID transactions

RavenDB dashboard
RavenDB has a colorful and intuitive user interface that makes it easy to navigate. (Source)

RavenDB is a multi-document database that supports ACID (Atomic, Consistency, Isolation, and Durability) transactions. This helps prevent data from accidentally falling into an inconsistent state. The platform is used by nationally recognized companies such as Toyota, Verizon, and Medicaid.

Why I Picked RavenDB

Aside from the visually appealing interface, I like that RavenDB supports ACID transactions. This ensures transactions can only change data in predictable ways and that those changes are always saved, even during a system crash.

RavenDB Standout Features and Integrations:

Features that make RavenDB shine include for a wide variety of network environments. You can use RavenDB in the cloud with AWS and Azure and on-premise with Windows, Linux, MacOS, and more.

Integrations with RavenDB are possible through pre-built tools and libraries, such as Fast Report and Bold BI, the latter of which lets you embed Analytics into your software applications, helping you gain insight into your business and products.

Pricing: From $789/core/year

Trial: Free versions available


  • Easy-to-use interface
  • ACID transactions ensure greater data consistency and time-saving
  • On-premise and cloud versions


  • Enterprise version is expensive
  • Lacking community support and documentation

Below is a list of alternative NoSQL databases that I also recommend:

  1. AstraDB – Best for real-time app building and scaling
  2. MarkLogic Server – Best for simplifying complex data
  3. Aerospike – Best for reducing server and cloud footprint
  4. Riak – Best for unstructured data management
  5. Apache Drill – Best schema-free database
  6. DataStax Enterprise – Best for zero server downtime
  7. Dgraph – Best for fault tolerance
  8. ScyllaDB – Fastest distributed database
  9. InterSystems Caché – Best for managing transactional and historical data

Selection Criteria for NoSQL Databases

Here are the evaluation criteria I used to develop my list of the best NoSQL databases.


To be considered for the Top 12, each tool had to offer these key database functionalities:

  • Data replication – This feature allows the database to copy and store multiple instances of data across multiple servers, minimizing the risk of data loss.
  • Horizontal scaling – This lets the database scale horizontally to other servers so as to spread out the workload beyond just one machine.
  • Support for different data types – This includes support for all kinds of structured, semi-structured, and unstructured data.


I selected tools that either had support for third-party tools and libraries or support for proprietary tools and libraries. Bonus points for both.


To be considered for my list, the software needed to have comprehensive written documentation and ample community support. Official training videos were a plus.

Pricing Models

To be eligible, they needed to offer a free version or a free trial. At the very least, a virtual playground to test snippets of code.

People Also Ask

Here are the three most common questions that people ask when searching for information on NoSQL databases.

Choose the Right NoSQL Database

According to a 2019 survey by Deloitte, only 18 percent of organizations were taking advantage of unstructured data.

Therefore, there’s a large opportunity for efficiency gains if you select better database tools that make it easier for your organization to collect and process large amounts of unstructured data.

This is why it’s important you understand what NoSQL databases are and their varying uses. Hopefully, this article will help you make the right choice for your organization.

Subscribe to the CTO Club newsletter to get the latest articles and insights on SaaS technology.

By Paulo Gardini Miguel

Paulo is the Director of Technology at the rapidly growing media tech company BWZ. Prior to that, he worked as a Software Engineering Manager and then Head Of Technology at Navegg, Latin America’s largest data marketplace, and as Full Stack Engineer at MapLink, which provides geolocation APIs as a service. Paulo draws insight from years of experience serving as an infrastructure architect, team leader, and product developer in rapidly scaling web environments. He’s driven to share his expertise with other technology leaders to help them build great teams, improve performance, optimize resources, and create foundations for scalability.