The 5 Fastest NoSQL Databases Every Data Science Professional Should Know About

Fast NoSQL Databases: Data is all around us and extremely plentiful. Just about everything that a consumer does generates data now. From posting to social media to purchasing groceries online for in-store pick up, modern-day databases need to be prepared to cope with these extreme data volumes.

The best way to cope with large data volumes is to use a distributed database capable of operating different nodes to partition data accordingly. That way, if one node goes down or is overloaded, the system can continue to run using other nodes with no problems. Fast NoSQL databases are also needed in order to keep up with the speed of the data streaming from multiple sources and also for real time processing of the data

Answering these challenges means using a fast NoSQL database that can handle partition tolerance seamlessly to create a great experience for customers while housing the information data scientists want.

What Is a NoSQL Database?

A NoSQL database does not mean that there is no relationship between data at all. NoSQL actually stands for “Not Only SQL.” This means that information stored in this type of database is not divided into various tables. That way, you can see all related data without specific restrictions.

NoSQL databases allow data scientists to view data in one structure. This enables the data processing to experience greater speeds and fewer performance lags. Completing multiple queries at once with these databases should be no problem and you won’t need to run joins.

Using a NoSQL database continues to grow in popularity because they scale extremely well and are ideal for distributed environments. Your team can rely on these databases to perform well under heavy workloads time and time again. 

Are NoSQL Databases Faster?

nosql databases are faster
NoSQL databases are faster and were designed for performance out of the box.

Yes, NoSQL databases are faster and designed for high-performance data processing. Developers created these non-relational databases out of a need for greater agility and performance while also scaling daily to meet the needs of ever-increasing data processing and storage.

NoSQL databases can help with real-time predictive analytics and meet the needs of billions of users.

As you go about your daily routines of surfing the internet and using mobile applications, you’re probably engaging with these lightning-fast databases. Some common uses for NoSQL databases include:

  • Social applications
  • Online ads
  • Data archiving

Why Are NoSQL Databases Faster?

The biggest reason that these databases are faster is that they “focus on using a very small set of database functionality,” according to Cameron Purdy, who used to work at Oracle.

Ultimately, the speed of your database will depend on how you’re using and querying that data. Some software engineers develop SQL applications that can act and function similarly to NoSQL, but it still leaves the question of the scalability of such ad hoc creations. And you’ll need to plan for longer development timelines to accommodate such engineering.

5 Fast NoSQL Databases

If you’re looking to increase the speed, reliability, and scalability of your database solutions, here’s a look at the nine fastest NoSQL databases available.

1. MongoDB

MongoDB is an excellent database for storing documents in JSON objects. Large companies like Uber and eBay use their services. Its ideal use cases include the following.

  1. Integration of hundreds of data sources with a unified data view
  2. The need for large read and write operations
  3. Storing clickstream data to analyze customer behavior

The company offers extensive online training and certification programs to help its users learn the database and use it to its fullest. 

2. Cassandra

Cassandra is an open-source NoSQL database. Facebook initially developed Cassandra but now it’s widely available and many companies use it because of its scalability. 

Cassandra is well-known for its ability to handle petabytes of information. It is also a great product for responding to thousands of requests at once.

Data scientists often choose Cassandra in the following scenarios.

  • Situations where they have more write operations than reading operations
  • Greater availability needs than consistency needs. Facebook built it to meet the needs of social networking, but the application would not do as well for banking
  • Fewer joins and aggregation database queries
  • Some examples of applications that lend themselves well to using Cassandra include weather data, order tracking, health tracking

3. Elasticsearch

Elasticsearch offers one of the best full-text search databases. It is open-source and highly scalable. You can use Elasticsearch when you need fuzzy matching.

Some major companies like Slack and Medium use Elasticsearch. The database is ideal if you’re looking to accomplish the following functionality.

  • Full-text search use cases
  • Chatbots to resolve queries, especially using fuzzy matching in the case of misspellings or poor syntax
  • Storing and analyzing log data
fast nosql databases
Choosing the right database will have an enormous impact on the speed of your project.

4. Amazon DynamoDB

Amazon’s product is not open source, but it is still highly scalable even with up to 10 trillion daily requests. It’s no surprise that many large companies like Snapchat and Samsung use Amazon DynamoDB.

This NoSQL database has two major use cases.

  1. Simple key-value queries with high volumes
  2. OLTP workloads that require highly consistent data, such as online banking or ticket booking

5. BangDB

BangDB is a very high-performance database in the world. It has been designed and developed from the ground up to deal with modern and emerging fast-moving data in real-time. It implements core features of a database like transaction, concurrency, WAL, indexing, etc. and at the same time implements AI, Graph processing, and Stream processing natively within the database for modern user cases

BangDB is ideal for the following use cases.

  1. Real-time data processing and analysis
  2. Random and real-time data access
  3. Predictive and enhanced data science with Graph

Scalable, Reliable Database Solutions

NoSQL databases offer some of the fastest, most reliable, and scalable solutions. Start building your modern data app today.

7 Tips on Choosing the Right NoSQL Database for Your SaaS Application

There are more than two dozen NoSQL databases on the market today. With so many options, it’s hard to know whether you’re choosing the right NoSQL database.

Ultimately, selecting a good SaaS database comes down to how you’re using the data. Each database uses a different architecture and therefore has different functions. So the first step in selecting a database is understanding the options. 

Tip 1: Learn the Advantages of NoSQL Databases

Before deciding that a NoSQL database is right for your SaaS application, learn more about the benefits and advantages of a NoSQL database.

  1. Scalability: NoSQL databases use low-cost commodity hardware that makes them easy to scale.
  2. Large data handling: The databases can handle large data volumes since they are distributed.
  3. Dynamic schemas: You don’t need schemas to begin working with data.
  4. Lower cost: Since these databases use commodity hardware clusters, they allow you to transact and store large data volumes at a low cost.
  5. Auto-sharding support: Spread data across any number of servers easily with NoSQL databases.

Tip 2: Know the Limitations of NoSQL Databases

Although NoSQL databases have many great advantages, they also have some limitations. One limitation is that they are not as reliable as relational databases. For example, most NoSQL databases do not support ACID natively, meaning you’ll need to use your own code to do so. 

You’ll need manual query language since your database isn’t compatible with SQL. This can slow down your system and make it more complex.

Finally, NoSQL is newer than relational databases, meaning they are not as stable and feature fewer capabilities as an emerging tech option. 

Tip 3: Understand the 4 Types of NoSQL Databases

Understanding the pros and cons of each database will help you make the right decision from the beginning.

Tip 4: Evaluate Current Structures and Transitions

If you have an existing web application that you’re looking to transition out of a relational database into a NoSQL database, consider your current structure and what that transition might look like. 

You might need several different NoSQL databases or microservices to transition out of your relational database without serious service disruptions or errors.

An incremental approach to database refactoring can ensure a seamless and simple transition. 

Make a plan for how to move away from your current database or databases in favor of the more agile NoSQL options. It might take some time to make the transition, but you’ll get faster response times and simpler scalability with the move.

Tip 5: Learn What NoSQL Databases Are Best At

Some scenarios lend themselves to the right NoSQL databases better than others. Here’s a look at some scenarios and application requirements that might lead to selecting this type of database.

Tip 6: Consider Long-term Use Cases

Future-proof your product by thinking through what your needs will be several years from now.

Avoid being shortsighted in the long-term use of your databases. Look down the road several years to consider how you might use the data in different ways and with increased volumes.

Choosing a database that only fits your needs today can mean a great deal of work and rework later on. Some types of NoSQL databases lend themselves to adapting and scaling better than others. Review possible needs as your company grow and develops to have a better understanding of your long-term needs.

Tip 7: Which is the right NoSQL Database for a Web Application?

With all the planning and research phases behind you, you can move on to choosing the right NoSQL database. There are more than two dozen available currently, but we’ve put together a listing of some of the best.

Download BangDB to Power Your SaaS Applications

BangDB is a powerful NoSQL database that can power various types of SaaS applications. With AI built-in, you can use deep learning to power custom experiences. Download BangDB Community now to learn more or consider an Enterprise license for added features and support.