Can NoSQL Database be Transactional?

Can NoSQL database be transactional? NoSQL databases started gaining traction and interest around 2006, making them 15 years old. When they started, they could not serve as a transactional database. That meant looking to relational databases anytime you needed transactional DB resources.

But like all technology, NoSQL is ever-evolving and building out new use cases. Some NoSQL databases can now serve as transactional databases but be careful when selecting one as not all include these features.

Get insights into what a transactional database is, changes to NoSQL databases to allow for transactions, and the options available to you when building out transactional applications.

What Is a Transactional Database?

The average technology user probably thinks little about how they can perform simple tasks. 

The data that a transactional database manages could be preferences, purchase data, or even information like a social media post. 

Transactional DBs generally have these three key features.

  1. Data accuracy: transactional DBs are generally ACID compliant (this stands for atomicity, consistency, isolation, and durability). That means that they can preserve large volumes of data accuracy in real-time. Historically, ACID compliance is one place where NoSQL databases have struggled. But new developments are helping overcome this to the point where some NoSQL databases can be ACID compliant.
  2. Data durability: Transactional databases ensure the durability of the data and in case of any failure/crash the DB can recover the data and brings the database back to the normal state. This is very critical when it comes to dealing with financial, accounting, (etc.) data.
  3. Flexible: users can edit data without touching other areas of other critical data sets. You can edit data without harming the system’s architecture. Users can easily pull transactional history even when data is housed in a limited context. NoSQL databases are far more flexible than relational databases, so this is not a challenge for this technology. 
  4. Speed: complete transactions in milliseconds with a transactional database. Speed should not be an issue when using one of these databases as you should be able to create queries and write data at incredible speeds. Speed is one of the greatest strengths of NoSQL databases, so it’s no surprise that these databases can meet this need. 

Ultimately, overcoming the ACID compliance need is the greatest hurdle for making NoSQL databases serve as transactional databases. 

Up until recently, the best transactional databases were relational databases, including SQLite, Oracle, MySQL, and Microsoft Access. But now let’s look into how NoSQL is changing to meet these needs for real-time data integrity and accuracy.


Without ACID transactions in NoSQL databases, many applications used SQL databases and NoSQL side-by-side. The transactional data went to the SQL database and high-volume data where data loss was acceptable went to the NoSQL database. 

And while this workaround ensured the application could capture all data, it made for challenging sharding requirements between the two databases. Plus, building out these applications took far longer than development teams wanted.

As NoSQL databases improve, data consistency is allowing it to be transactional. In BangDB, all single API calls are ACID, allowing it to serve as a transactional database. 

Options Available for NoSQL Transactional DBS

When evaluating NoSQL transactional DBs, you want to primarily look for ACID compliance. Several NoSQL databases now handle ACID compliance. We’ll explain which ones to help you in finding the best transactional DB for your application.

1. MongoDB

This open-source database powers many web and mobile applications. It allows for single-shard transactions with ACID guarantees. The system does support multi-document ACID transactions. According to MongoDB, its transactions have four limitations.

2. RavenDB

RavenDB was the first to offer a NoSQL database with ACIDicity across entire clusters. While transactions are distributed, they are still ACID compliant. It uses a custom-built storage engine that it calls Voron. It rolls all calls into one package to simplify the ACID transaction process to ensure performance. 

Free and Open Source NoSQL Databases. When Free Isn’t Really Free

Open-source & Free NoSQL databases are not truly free. While the code base is readily available, it doesn’t mean that it’s the right foundation for your application. And if that’s the case, that free NoSQL database could end up costing you a great deal.

  • Open-source databases are not necessarily free 
  • Many open source databases exclude parts of the codebase without a paying subscription
  • Some open-source license agreements have commercial use exclusions or limitations
  • Open source licenses can carry serious restrictions
open source NoSQL database

NoSQL stands for not only SQL, which is why you can use these databases to house structured, unstructured, and semi-structured data together in one place. 

You can retrieve the data using SQL or other means. To do so, the databases use developer-friendly API interfaces to perform DML and CRUD operations. You can execute these operations using various programming languages.

Is an Open Source NoSQL Database Right for Me?

Determining the right NoSQL database to meet your needs means digging deep into project requirements and understanding licensing. If you’re unsure about how to find the right database for your needs, contact us. We will work with you to determine the best format for your data.

NoSQL or SQL Database: What is Best for My Application?

There is no hard and fast rule on when to use a SQL database versus when to use a NoSQL database. Instead, determining your cloud data storage components requires taking a deep dive into the data you’ll be reading, writing, and storing. Answering the questions NoSQL or SQL what is best for my application will take several steps.

But you also need to consider what you need your data to do for you. As the expectations for data processing continue to increase, SQL databases are struggling to keep up. That’s why you’re likely to hear more about NoSQL and its capabilities.

How to Decide Between a Relational and NoSQL Database

To answer the question of what is best for my application, you need to evaluate several factors. We’ll walk you through these factors and explain how they could impact your decision between SQL and NoSQL.

1. Data Structure

The most important consideration when evaluating which is best SQL or NoSQL is in evaluating your data’s structure. 

When most of your data is structured, you should use a SQL database. Applications that run transactions such as e-commerce platforms, CRMs, and accounting systems lend themselves to SQL well. 

2. NoSQL vs SQL for Data Queries

Once you understand your data’s structure, you need to move on to evaluating your need for data queries. But the question isn’t just whether you need to query data, but how fast you need those queries to execute and who is responsible for executing such queries.

Due to the structure within SQL databases, you can query data with great ease. Although tedious, the SQL language has been around for decades. The language is mature and has plenty of resources to support it.

As a result, SQL databases are incredibly easy to query and get data back from quickly. The language is lightweight, and although tedious, it’s easy to learn. 

Because NoSQL is flexible and lacks that tidy organized structure, querying the data can present some challenges. It’s certainly possible to query these databases, but it isn’t as efficient and takes a bit more expertise. 

Developers that created the concept for NoSQL were seeking out flexible, scalable solutions. Their goal was not to find an efficient query structure. 

The result of the flexibility and scalability of NoSQL is that you’ll need to undergo more data processing to complete a query. Some developers build in the ability to query their data within the application layer instead of the database layer to simplify the process. 

But as NoSQL becomes more popular, many developers and data scientists are skilled at efficiently querying the data. Deciding how and how often to query your data will answer the question should I use SQL or NoSQL?

3. SQL vs NoSQL Database Scalability

SQL and NoSQL databases scale differently. So before you build out your application, consider your growth needs. How will your data expand and transform in the future of your application?

SQL databases only scale vertically, which means you need to keep all your data on one server and upgrade the server to meet your needs. That means increasing RAM, SSD, or CPU to accommodate changes. Protecting the integrity of your data means keeping it all on one server. 

However, NoSQL databases can scale horizontally, which means you can add additional servers to meet your growing needs. The ability to scale horizontally is one of the greatest strengths of a NoSQL database compared to a SQL database.

NoSQL can scale so well because of its lack of structured data. Each object within the database is independent, meaning the objects can be in different server locations and don’t need to be linked for the database to function. But SQL data is organized in rows and columns that rely on one another for their relational data. 

The best way to determine your scaling needs for your database is to evaluate your business goals. And when you do this, don’t look a couple of years in the future, but as far as you possibly can because changing databases for your application will be a timely and costly initiative. 

NoSQL or SQL what is best for my application?

Where SQL and NoSQL Databases Converge

As NoSQL databases develop and mature, they’re blurring the lines between NoSQL and SQL. Remember that NoSQL stands for not only SQL. That means that some data within these databases can be structured. 

Many NoSQL databases now offer a convergence of structured and unstructured data. For example, many developers now look at MongoDB SQL or NoSQL because you have options now even once you select a database partner. Many NoSQL databases can now offer ACID transactions to meet your needs.

BangDB offers a multi-model approach to data and layers in AI to make data easier to query. Machine learning is transforming NoSQL databases to make them more intelligent and simpler to operate.

Many applications that could only run on SQL databases before can now transition to NoSQL thanks to the power of artificial intelligence. 

The question today is less about SQL vs. NoSQL and more about evaluating which NoSQL database is right for your application. That’s because, given the trajectory of data logging, SQL databases cannot house the amount of ever-growing data efficiently. Very few applications require SQL databases today thanks to new developments and innovations in the NoSQL marketplace.

Data integrity within NoSQL continues to improve but is one area where SQL reigns supreme. However, NoSQL is far more flexible, scalable, and poised for rapid iteration and development.

Still asking the question: NoSQL or SQL what is best for my application? Contact our team to learn more about what the BangDB database can do.