Why use a NoSQL database?
NoSQL databases emerged in 2009 as popular websites started scaling up. At the time, none of the databases available could scale enough to meet the demands of the marketplace.
NoSQL is a non-relational database technology (which is primarily schema-less) that can be used in massive data applications where data is unstructured.
In this scenario, the architecture uses collections and documents instead of tables and rows. It’s also essential because modern applications need much more than a single database to function properly.
However, with databases like MongoDB, data consumption tends to be high due to denormalization. Furthermore, developers are moving away from MongoDB because of different issues with the data management software.
When it comes to NoSQL databases, the real difficulty is knowing which database is suitable to solve your specific problems. So, we went to work, dug through the data, and came up with a list of the top 11 MongoDB alternatives (both SQL and NoSQL and free and paid options) that developers and data engineers should know about.
NoSQL MongoDB alternatives
1. Apache Cassandra
If you want high availability and scalability while ensuring performance, Apache Cassandra is the answer.
This open-source NoSQL database enables operational simplicity and provides support for replication across multiple data centers and cloud availability zones. In this case, data is replicated to multiple nodes to create a fault-tolerant system.
Initially developed for Facebook, you can deploy Apache Cassandra across multiple servers pretty quickly. As every node in the cluster is separate, you don’t have to worry about any bottlenecks in the network.
However, some users report that high availability is far from consistent and that performance can be unpredictable.
TL;DR: Apache Cassandra is a heavyweight MongoDB alternative that’s ideal for enterprises with large datasets. However, performance levels aren’t guaranteed or consistent, so you must prepare for that.
Apache Cassandra pricing: customized to your needs, and a free version is available.
Redis is an open-source NoSQL database that ensures high availability by adopting Active-Active and Active-Passive geographically distributed architectures.
Like Apache Cassandra, Redis comes with linearly scaling high performance and excellent built-in search capabilities.
Redis is fast and supports various data structures, including:
- geospatial indexes with radius queries
- sorted sets with range queries
However, users report that the enterprise version is expensive and that you have to log in to each host to execute commands.
TL;DR: Redis is best for data and development teams looking for speed. However, it's better suited for larger enterprises with big budgets.
Redis pricing: starts at $5 per month (100MB and four datasets), and a 30MB free tier is available.
OrientDB (now supported by SAP) is an open-source NoSQL multi-model (or second-generation) database.
If you’re into graph databases, this might be the solution for you. Whenever you leverage its True Graph Engine, you won’t have to implement multiple systems or handle other data types.
OrientDB is an excellent choice for modeling data with complex relationships, and, unlike some of the other MongoDB alternatives, it provides free clustering support.
However, users report poor documentation, compatibility issues, and high hosting costs.
TL;DR: OrientDB is a great option for teams looking to unlock the true power of graph databases. However, you might run into some issues when it comes to documentation and compatibility.
OrientDB pricing: starts at $5,970, and a free community edition is also available.
DynamoDB is Amazon’s key-value, serverless database that helps enterprises realize single-digit millisecond performance at any scale.
This fully managed, multi-master & multi-region database comes with security, in-memory caching, and built-in backup and restore.
What’s great about this MongoDB competitor is that it can handle a whopping 10 trillion requests a day and support peaks of more than 20 million requests a second.
However, if you’re not familiar with NoSQL, you’ll have to contend with a significant learning curve. It’s also expensive but worth the money if you’re running a global scale application.
TL;DR: Amazon DynamoDB is an excellent option for global applications with a ton of users. However, if you’re not comfortable with NoSQL, you might want to try something else (keep reading!).
Amazon DynamoDB pricing: is based on on-demand capacity and provisioned capacity. A free version and a free trial are also available.
You can deploy this document-oriented database as a standalone application framework or with a high-volume distributed application, especially web applications that handle massive amounts of loosely structured data.
CouchDB also stores all data in JSON format; authentication and session support ensures durability and security.
However, users report that there’s no full-stack search and that the UI can be confusing.
TL;DR: CouchDB is perfect if you’re handling an enormous amount of loosely structured data. However, those unfamiliar with this lightweight MongoDB alternative might find it a little confusing in the beginning.
Apache CouchDB pricing: free.
ArangoDB is an open-source NoSQL, multi-model, graph database used to ensure the high availability of high-performance applications. It has a flexible data model for graphs, key values, documents, and SQL-like query language.
It's also supported by a large and vibrant community and comes with a built-in microservices framework and a search engine.
When you use ArangoDB, you can perform graph analytics queries while reducing the number of database technologies used in production.
TL;DR: ArangoDB helps developers build highly available high-performance applications. However, you have to learn its own AQL language.
ArangoDB pricing: the enterprise version is customizable to your specific needs, and a free version is also available.
RethinkDB is an open-source, distributed database built to store JSON documents. Ideal for multiregional, multi-datacenter deployments, you can scale up to multiple machines with little to no effort.
If you’re building real-time apps, it’s worth looking into RethinkDB, but unfortunately, the company behind RethinkDB shut down in 2016 and is now part of the Linux Foundation. So, it’s not going to be supported with regular updates and upgrades.
TL;DR: RethinkDB is perfect for development teams working on multiregional, multi-datacenter deployments.
RethinkDB pricing: free and open source.
SQL MongoDB alternatives
MySQL is a leading MongoDB alternative that is lightweight and often used in PHP & Java web applications.
MySQL is known for reliability and affordability. If you’re looking for data security and strong transactional support, this might be the right choice for you.
However, users report problems performing complex joins, scaling, and more. So, it might help to do your own research before committing.
TL;DR: MySQL is probably the most popular database on the planet that’s easy to learn, and the enterprise version won’t break the bank. However, there are a lot of issues reported by users that are worth looking into before committing.
MySQL pricing: based on a per-user pricing model, and a free trial is available.
PostgreSQL is a popular open source, post-relational database that runs on just about every operating system.
Because of its complexity and power, PostgreSQL is better suited for large enterprise applications.
However, users report that the installation and configuration are pretty complex and unsuitable for some data types like timeseries data.
TL;DR: If you’re working with both structured and unstructured data at scale, you might want to check out PostgreSQL. However, if you’re working on IoT projects with timeseries data, it’s best to look elsewhere.
PostgreSQL pricing: free and open source.
Elasticsearch is a cloud-based RESTful search & analytics engine based on Apache Lucene. Highly suitable for searching text for NLP projects, it can also store your data and search it in real-time (almost anyway).
However, users report that a server crash sometimes results in a total loss of data. As a result, Elasticsearch may not be the best choice when you’re working on critical data.
This database comes with a whole host of libraries for many programming languages like:
This makes it relatively easy for developers to integrate with Elasticsearch (check out how you can integrate Elasticsearch with Panoply).
TL;DR: Elasticsearch works well for voice recognition and NLP projects. However, it’s best not to store any mission-critical data as server crashes have been known to happen.
Elasticsearch pricing: starts at $16 per month, and a free trial is available.
CockroachDB allows developers to scale databases and deploy them across applications at any time and anywhere. Even better, these applications can also survive data center-scale outages.
The best part about CockroachDB is that you can scale business-critical applications and ensure that they are always available (and correct).
However, users report that CockroachDB lacks capabilities to create SQL functions, is slow at times, and comes with a steep learning curve.
TL;DR: CockroachDB is excellent for developers scaling business-critical applications, but users consistently report some performance issues worth looking into.
CockroachDB pricing: follows a per feature pricing model, and a free trial is available.
Comparing MongoDB alternatives
When it comes to relational and distributed databases, we’re spoiled for choice. However, it’s vital to ensure that they are actively supported and scale with you as your project grows.
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