Does NoSQL Mean Cloud? Best NoSQL Cloud Database Services in 2022

Just like traditional databases, not all NoSQL databases are cloud databases. A cloud database runs on a cloud virtual machine. This machine can be on a public, private or hybrid cloud. Or, it can be part of a database-as-a-service (DBaaS) offering.  

DBaaS is the equivalent of software-as-a-service (SaaS) where you subscribe and pay as you go. The platform manages the provisioning, maintenance, and performance. The service provider makes it simple to use the database. 

However, if you choose to host the database yourself on a private, public, or hybrid cloud, you’ll be responsible for handling the upkeep, security, and performance of the database. 

Want to learn more about NoSQL cloud options? This article will explain the difference between DBaaS, and self-hosting and provide an overview of the best NoSQL cloud database options.

Is NoSQL a Cloud Database?

No, not necessarily. Some NoSQL databases include all the structure and code that you need but they do not host it on the cloud for you. While you can then use host databases on public, private, or hybrid cloud servers, they are not necessarily natively cloud databases.

To be a cloud database, you’re looking for a database-as-a-service provider which means you don’t have to host the database on your own local or cloud servers.

Benefits of DBaaS

A NoSQL cloud database service has many great benefits. Here’s a look at a few of those top benefits.

  • Easy, yet controlled access from anywhere
  • Agility to manage the data and software development process
  • Scalability to meet your ongoing growth needs
  • Outstanding performance 
  • Reduction in manual labor for your team
  • Reliability thanks to regular backups
  • Disaster recovery
nosql cloud database

NoSQL Cloud Database Service Use Cases

There are several NoSQL cloud database use cases where you’ll appreciate having a database-as-a-service provider. Here are a few examples.

  • Projects that require large data volume
  • Cloud-native applications
  • You’re planning to handle high scale traffic
  • The traffic will be distributed geographically
  • It requires real-time transaction processing
  • You’re migrating from a legacy database
  • The project includes a mobile application
  • You’re using the database to power internet of things application
  • The application requires caching
  • You’ll be relying heavily on analytics

Key Considerations for Cloud Databases

As you prepare for finding the best NoSQL cloud database, review these considerations to make the best selection possible.

1. Provider Options

Some databases can only run on a specific cloud provider, such as Amazon Web Services (AWS) or Google. If you want to have cloud provider options, have that discussion with a representative from the database provider you’re considering. 

Some of the most influential aspects of deciding on a provider are based on your existing relationships, compatibility with other technology, etc.

2. Technology

Make sure that a NoSQL database will work for your application. Some databases are transactional while others are not. Some integrate AI, others use outside AI products and still, others have no AI capabilities. Learn the technology limitations and options for the database before subscribing.  

If your in-house resources are only comfortable working in SQL, also consider what training and preparation moving to NoSQL will require. Consider your team’s skills with different programming languages to choose a provider that best fits those skills.

nosql cloud databse

3. Database management

Before selecting a self-managed database, consider your in-house resources. If you don’t have the skills to oversee a database, you’ll need to ensure you select a fully managed database. Otherwise, you might find that you end up with more overhead to hire team members capable of self-management, which could cost more.

4. Pricing

Some database services base their pricing on usage. This makes new projects more affordable since you’ll only need to carve out a small amount of space on a server to house your application. Before signing up, be sure you understand the ins and outs of the pricing structure so you know if it is license-based or usage-based.

5. Security

While a fully managed database-as-a-service has many great benefits, you want to be sure it isn’t opening your organization up to security risks. DBaaS providers must meet stringent regulatory requirements to secure customer data. This can be one of the greatest benefits of DBaaS is that you don’t have to assume the risk of security concerns.

6. Added features

Many database-as-a-service providers add-in features you might not get if you hosted the database yourself. These can include additional reporting, automatic connections to other services, and more.

Best NoSQL Cloud Database

With a greater understanding of how a NoSQL database can be a cloud database, you’re ready to start reviewing the options available to you.

1. BangDB

BangDB is a multi-model NoSQL database that enables you to store all types of data. It offers stream processing for real-time continuous data and has native AI capabilities so you can train and predict within the database. 

  • Double the performance of other leading databases
  • Native AI offers faster machine learning
  • Complex event processing helps you find real-time data patterns
  • Incredible statistics for fast queries
  • ACID-compliant for transactional needs
  • Supports rich query

BangDB is not a fully managed database-as-a-service offering. Be sure to learn more about the licensing before selecting BangDB.

2. MongoDB

Is MongoDB a cloud? Yes, MongoDB Atlas is a fully managed cloud database designed for modern applications. It is a key-value NoSQL database that stores and retrieves data as JSON documents. Some of the benefits of MongoDB include:

  • Built-in intelligence
  • Strong querying capabilities
  • Good analytics
  • Flexible document schemas
  • Uptime is excellent

Despite being an excellent option for a cloud-based NoSQL database, MongoDB does have some limitations.

3. Azure Cosmos DB

This NoSQL database has open APIs so you can easily scale your applications. Azure Cosmos DB is one of the best NoSQL cloud database options The free version allows for up to 25BG of storage and 1,000 request units per second. The database’s benefits include:

  • Nearly perfect availability
  • Low latency
  • Globally distributed database
  • SSD backed storage
  • Reserved throughput model
  • Ideal for IoT, social applications, mobile apps, and gaming
  • Database-as-a-service from a well-known and respected name in the industry

4. Oracle NoSQL Cloud Database

Oracle’s NoSQL cloud database offers the ability to store data in columns or key-value format. The database has a free option to help you get started and test out whether the database is right for you. You’ll also experience these great benefits.

  • Single-digit millisecond response times
  • High availability
  • ACID-compliant
  • Pay-per-use pricing
  • Compatible with on-premises Oracle NoSQL database

5. Amazon DynamoDB

Amazon Dynamo DB is a key-value and document NoSQL database. It started as a solution to Amazon’s need to handle larger traffic volumes to its service during heavier shopping seasons, such as during the holidays. Then it went public for others to use starting in 2012. It is a popular option for public cloud databases. 

  • Integrates well with other Amazon technology
  • Fully managed cloud NoSQL database
  • Able to handle 10 trillion requests per day or even 20 million requests per second

Although DynamoDB fits well into the family of Amazon technology services, it isn’t as ideal if you use other services and technology. It also lacks ACID compliance, which means it is not a transactional database.

Further Reading:


Moving From SQL to NoSQL Database: An In-Depth Handbook

Relational databases were created back in the ’70s. Imagine trying to play a 4k movie on 70’s television, or checking your favorite news app on a phone from the 70s… 

Impossible, obviously.

For almost every area of modern life, you use modern technology because it just makes sense. The same is true for your business tech. 

So we thought it was time to show you what it takes to migrate from your outdated SQL system to something more scalable, flexible, and technologically sound.

Steps to Switch Database Systems:

  1. Choose a NoSQL database provider
  2. Familiarize with the new system
  3. Conceptualize how you will represent your data
  4. Make the leap from SQL to NoSQL
  5. Rewrite your application code for NoSQL

The process can seem daunting at first, but many major companies, such as Marriott, Ryanair, Gannett, Art. sy, Foursquare, and more started with relational systems and later upgraded to support their exponential growth. 

In the rest of this article, I’ll walk you step-by-step through the process so you know exactly how it works.

Step 1: Choose a NoSQL Database Provider

Before you can move anything, you’ll need a service provider. You can learn more about some of the fastest NoSQL providers here. If you just want to see an overview of some of our top choices, here are our favorites:

  • BangDB
  • MongoDB
  • Cassandra
  • ElasticSearch
  • Amazon DynamoDB

The database provider you choose should be based on what you need to accomplish with your application; however, BangDB is considered one of the fastest, easiest, and most reliable providers in existence, so it is always a good choice in our opinion.

Step 2: Familiarize with the New Database System

Once you’ve chosen a service provider, you need to understand a little about their solution. You don’t have to be an expert in NoSQL, but it helps to have an idea of what that service is capable of and how you can implement it for your application.

  • Download the database system if possible
  • Read some of the manuals and online tutorials
  • Use the system for one or more test projects

Start by downloading the system if it has a free version. BangDB (mentioned above) has a completely free, open-source option that can be upgraded for Enterprise use and additional functionality later on. That means you can download it, learn it, and test it before going all-in.

Most service providers offer online tutorials that are really insightful and can help you avoid common challenges as you make your move. You can read these yourself or have your developers review them to make sure they *get it* before diving into the deep end of the pool.

We also recommend putting your new database service to use on small test projects before migrating your entire application. Hands-on experience will help you and your developers get a feel for the power you’re about to have in the palm of your hands, and as you’ve probably heard… 

“With great power comes great responsibility.”


Even though migrating data from one system to another is actually pretty simple, it is important to get familiar with the new system before you make the move.

Looking for an innovative NoSQL solution?

Step 3: Conceptualize How You Will Represent Your Data

Another pre-move consideration is how you plan to represent your data in the new system. You have several options, and the right one for your business will depend on the capabilities you need. 

Common NoSQL Data Store Options:

  • Key-Value Pair
  • Document
  • Column
  • Graph

Key-Value Pair
In this database setup, you will store key-value pairs with a record. A key can be a numeric or string value and needs to be unique within its record.

A document store is used for keeping semi-structured data. Data in a document store is encoded in standard formats such as XML, JSON, YAML, and BSON. 

Instead of storing data in rows, this database type stores information in columns which simplifies the aggregation process to make it easier to analyze information quickly. Columns can be unlimited in number, and can also be grouped into logical “families” with reading and writing carried out in columns rather than rows.

The graph is useful for applications that represent data in graph format where information is interconnected. This type of database implements nodes, edges, and properties. 

Start to think about what you need your application to do because life is much easier when you migrate to a database solution that makes natural sense for the goals of your app.

Step 4: Make the Leap from SQL to NoSQL

You’re finally ready to migrate from your old relational system to your new, improved NoSQL. For many applications, this process is relatively easy.

For example, most migrations can make use of SELECT * FROM statements against the original database. After that, they can then be loaded into the NoSQL database using whatever language you choose.

That said, each type of NoSQL is somewhat different, so your migration process may vary. To understand the exact steps to load your data into your new system, you will need to consult the service company’s tutorials or documentation.

For information on BangDB’s migration process, see the Developer’s Manual page here.

Step 5: Rewrite Your Application Code for NoSQL

Once your data has been moved from SQL to NoSQL, then the final step is to rewrite your application code so that it can query the NoSQL database with statements like insert() or find().

You will want to test your application before launch to ensure everything functions as expected, and you will also want to stage your application launch following similar due diligence steps as you would normally take with your old relational system.

In addition, you will also want to spend time learning your new database administration tools so you have a strong understanding of the different options available to you, and how everything works.

Migration Challenges to Expect

Before you start your SQL to NoSQL data migration, it is helpful to have an idea of some of the common challenges others have faced.

Moving Large Volumes of Users

If you’ve been in business a while, you may already have a large number of users. Sometimes that can cause hesitation and reluctance when it comes to moving from one place to another. While the new system may work flawlessly, that doesn’t mean problems never occur. 

The Solution? Start with a phased migration where you move a small number of users such as 3-5% and then 10-15%, and then 30-40%. Once you’ve done this several times and you feel comfortable with the process, then you can remove all of the remaining users at once with confidence.

Data Optimization

Optimizing data is another potential challenge companies sometimes face. Migrating from a SQL to NoSQL database isn’t particularly difficult; however, the new system needs to be optimized for your application. To ensure your new system is optimized for your application, you will need to know which queries your app runs and which queries you want to optimize the data store for so you can avoid any speed problems.

Choosing the Right Database Design

If you’ve never worked with NoSQL before, then it can be challenging to conceptualize how your data might be represented in the new system. Solving this problem requires spending some time understanding the different data models by reading through tutorials or working with a developer.

Choosing the Best Service Provider

There are many options to choose from. We’ve discussed quite a few of them on our blog, and the right one for your business will depend on your needs. 

That said, BangDB is considered one of the most flexible, easiest to use, open-source database service providers. Not only that, but it comes with a completely free version that can be downloaded and tested before migrating any data at all.

For those reasons, we recommend having a look at BangDB to find out if it might be right for you. If it turns out to be the exact right solution, then you can download BangDB here for free.

Further Reading:

The Hidden Benefits of Real Time NoSQL Database Architecture for Applications

The NoSQL database architecture provides many benefits over other, more traditional options like relational SQL databases. Not only does NoSQL handle larger volumes of information, but it is scalable, easier to update, friendlier for developers, and can use cloud infrastructure for zero downtime.

The primary benefits of NoSQL are numerous, but what about the hidden benefits that nobody really talks about? That’s what we’ll cover in the rest of this article.

Real-Time NoSQL Database Hidden Benefits:

  • Support huge volumes of users (in the tens of thousands and beyond)
  • Improve user experience with extremely responsive data points
  • Always ready for rapid updates and fast feature additions
  • Synchronize data with cloud platforms for mobile support

When you work with real-time applications, each of these points becomes a huge advantage that improves the user experience as well as the speed and efficiency of backend support.

Even improving just one area can make NoSQL the better choice over other options depending on the size of your business and its goals. 

Now, let’s take a closer look at how each of these points equates to more productivity, increased platform engagement, lower costs, and higher profits.

Why Scalability Matters for Application Development

At the start of an application’s lifecycle, scalability may not seem that important. The aim of a minimum viable product (MVP) is to move fast, enter the market early, test your idea, and get valuable feedback from users. But what happens when that feedback is positive?

Suddenly, you’ve got proof of concept and room to grow. That means your application can be scaled up without reservation since you have confirmation that the people it was designed for like your offer and want more.

If you developed your app with NoSQL from the start, then you can probably dive in and scale up with ease. But if you chose a more constrained option like a relational database, then you may discover you run into limitations since these systems weren’t designed for the kind of exponential expansion that happens in modern software applications.

Relational Databases – It’s Like Chiseling Notes on an Ancient Stone Tablet

Don’t get me wrong, relational databases have their uses, but they were designed before the IoT existed, and they were never meant to scale up for hundreds of thousands of users who want access to real-time information. 

For that reason, trying to get a relational database to function how you want is like loading Fortnite on a 90’s Windows OS (it’s not happening).

Relational Databases Are Best For:

  • Simplicity
  • Data Accuracy
  • High Security
  • Standardization

Although relational options are considered the “standard” when it comes to managing data, they’re starting to show their age as faster, more scalable, and more reliable options such as NoSQL start to emerge.

Looking for an innovative NoSQL solution?

The NoSQL Database was Designed with Exponential Growth in Mind

NoSQL stands for “not only SQL,” meaning you can empower your app with the capabilities of an SQL database, and with functionality that extends beyond relational limitations.

Today, having the power to manipulate and retrieve data at almost instantaneous speeds is the expectation rather than the exception. 

Once an app goes live, it might be used by millions of people, all of which expect a flawless and smooth experience. To make that happen, it makes sense to start from a scalable infrastructure rather than trying to upgrade an outdated system later on.

How Exactly Does Cloud Infrastructure Improve User Experience

In addition to scalability, NoSQL solutions are empowered by cloud services that add a wealth of benefits to the current developmental environment. 

Cloud Infrastructure:

  • On-demand scaling to support higher user volume
  • Globally operational apps for a worldwide customer base
  • 24-7 availability and virtually zero downtime
  • Synchronize seamlessly to support mobile users
  • Minimizes the cost of infrastructure
  • Dramatically speeds up a time to market

When combined with the ability to rapidly return real-time data at scale, a cloud infrastructure ensures the smoothest user experience possible. 

Instead of frustrating customers due to downtime or disconnects, or limiting your app to specific locations, cloud capacity transforms you from the Flintstones into the Jetsons. Suddenly, you can engage users almost anywhere on the planet.

Additional Hidden Benefits of a Real-Time NoSQL Database

Beyond the obvious benefits of leveraging modern systems to operate at scale and serve more people faster, there are a few other hidden gems worth noting.

  • Eases the workload burden for developers
  • Improves the testing and iteration process
  • Results in greater overall profit potential

When developers have the tools they need to build effortless solutions and make quick changes, then productivity increases and their overall workload decreases.  This results in more satisfaction with their ability to manipulate data and work with real-time feedback. In return, developers work harder for your business because they can reap the rewards of an unobstructed workflow.

In addition, simplified feature implementation and fast turnaround on upgrades speed up the overall testing and iteration process for rolling out new app concepts. Faster iterations decrease time-to-market, which opens up pathways to higher profits going forward. 

Finally, as a result of faster time-to-market, and faster testing, the end-user experience improves substantially. This leads to a steady flow of new and returning customers who are happy to make purchases at higher prices, therefore, increasing total profit potential.

How to Get Started With NoSQL

real time nosql databases

When you’re ready to develop your real-time application and you want to start from a future-proof NoSQL foundation, then you have several options available to you. 

Here are four of the best NoSQL databases around:


Powered by native artificial intelligence (AI), BangDB’s real time NoSQL database solutions are exceedingly useful for a variety of modern apps. Not only is it among the fastest, simplest, and most scalable choices available, but it is free with up to three licenses, and can be upgraded as you become more profitable and as your business grows.


Another solid option, MongoDB is a good choice when you need to store documents in JSON. While not as flexible or capable as BangDB, MongoDB offers a variety of training and certification programs to help users get the most out of their services.


If you’re looking for an open-source solution, then RavenDB could be the right option for you. RavenDB offers a fast NoSQL database that can be set up for on-premise use or cloud-based applications.


Last but not least, HBase is another open-source option with a high potential for scalability. Because it is written in JAVA, and because of its capability to store data for billions of users with rapid access, HBase has been used by large social platforms such as Pinterest and HubSpot.

The Best Real-Time NoSQL Database for Modern Applications

Quite a few options exist, and there are benefits and drawbacks to each. BangDB is currently considered the fastest, easiest, and most powerful machine-learning, deep-insight NoSQL database around.

If you are looking for the best overall option, then you will want to tap into the power of the BangDB architecture; however, any of the solutions mentioned above can help your business grow depending on your needs. 

To start your app development with BangDB for free (with unlimited use), go here to Download BangDB now.

Further reading:

Best NoSQL Databases for IoT Applications: Commercial and Open Source

The Internet of Things (IoT) requires certain database characteristics. IoT encompasses a wide range of technology from smart objects to empowering RFID systems. Astoundingly, the IoT worldwide revenue is $34.8 billion and growing. The challenges of using a NoSQL database for IoT come more from the development process than from the database itself.

Some developers get lulled into thinking they’ll put all the necessary data into a NoSQL database and figure out the schema later. But if you don’t create some form of structure for your data even within NoSQL, you risk the following challenges.

  1. Data loss
  2. Poor data readability
  3. Pipeline inefficiencies

The extreme flexibility of NoSQL is a great advantage, but it can become a disadvantage if you don’t plan how to use the data. 

Key Considerations When Selecting an IoT Database

When building an IoT application, you should consider these important factors in the database you select.

  1. Size, scale, and indexing capabilities
  2. Stream processing
  3. Flexible schema
  4. Running querying support
  5. Sliding window
  6. Cost

But you’ll also want to think about the types of data you’ll be dealing with. Some examples of data types include.

  1. Log data
  2. RFID, geologic
  3. Identifiers or addresses
  4. Sensor data
  5. Much, much more

Seeking the Best NoSQL Database for IoT?


InfluxDB is another option that launched within the last decade. It was published in 2013 and is a key-value database. It uses the Go programming language and is optimized to handle time-series data. It has many IoT benefits, including:

  • Indexable series
  • Built-in linear interpolation for missing data
  • Calculates aggregates based on continuous queries
  • SQL-like query language to help automate data downsampling


MongoDB is another NoSQL database option. It is free and open-source and is a document-based database. You can store all types of data and analyze it in real-time. Additionally, developers enjoy how they can change the schema as needed.

Experience BangDB for IoT Applications

Thousands of users have downloaded BangDB and many reports it is excellent for IoT applications. Learn more about it by downloading the NoSQL database today.


Beyond NoSQL Database: Why AI Is Needed within NoSQL for Modern Use Cases

Those familiar with traditional NoSQL databases know that scalability, flexibility, and speed are primary concerns. More data retrieved faster leads to actionable insights for developers and a better end-user experience.

Despite their growing popularity, NoSQL databases are challenged in four core competencies that limit their performance and function. afgsdfgsdf sasasas vfvfv

NoSQL Database Core Competency Limitations:

  • Complexity Limitations
  • Scalability Limitations
  • Rigidity Limitations
  • Cost Limitations

As long as these limitations continue, NoSQL databases cannot achieve their full performance capacity. Unfortunately, as an emerging technology, few solutions exist to overcome these problems today.

It is for this reason that artificial intelligence within NoSQL databases is needed for modern use cases. More on that in a moment. 

First, let’s look at how NoSQL databases work together with artificial intelligence for modern use cases right now. This will give you a broader picture of how AI convergence changes everything.

What is an AI Database?

AI Database Solution

The elimination of silos and the convergence of AI within the database means there is no need to integrate heterogeneous items individually. Instead, an AI database uses a single distributed layer to free up resources and empower the database to rapidly scale where scaling was nearly impossible before.

AI Databases Are Self-Serving

One of the biggest limitations of traditional NoSQL databases is the necessity of developers and coding. With AI databases, data is streamed in real-time which removes the need for an added analytic layer. In addition, the AI’s machine learning capacities train and deploy fast, and leverage abstractions for reuse to decrease build times. This means that adding features no longer requires an extensive backlog of coding. Instead, regular people can operate the database quickly and easily.

AI Databases Are Affordable

Dealing with big iron appliances or consultants can add hundreds of thousands, if not millions to startup costs. AI databases, on the other hand, can be cloud-based and allow you to start small and pay as you grow. Since AI databases are based on commodity (off-the-shelf) hardware, and because they do not require expert

Today, BangDB offers one of the most reliable and scalable AI database solutions available anywhere. To get started for free with unlimited use, go here to Download BangDB now and build your AI-powered app today.

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.

Processing Structured and Unstructured Data in a NoSQL Database – the Basic Rules

Structured and unstructured data are not an either-or scenario. Instead, it’s a matter of matching the data type to your application and its needs. Each serves a purpose and has advantages and disadvantages.

Get a better idea of when to use structured and unstructured data and some of the benefits of each. 

What is Structured Data?

Structured data generally lives within a relational database. Big data is processed using relational/SQL databases where each field of information is in length-delimited data.

Some data is machine-generated. This might include information from the following sources.

  • Satellite imagery that powers weather information or informs military movements
  • Scientific information, such as seismic images or space exploration data
  • Surveillance photos or video
  • Data from sensors, such as traffic or weather data

What’s the Difference Between Structured and Non-structured Data?

nosql databases can process both structured and unstructured data
The biggest difference between structured and non-structured data lies with the analytics.

The obvious difference is in how and where the data is stored. Unstructured/Non-structured data is generally in a NoSQL database while structured data is in a relational/SQL database. 

But the difference in the experience with the data is in analytics. Data processing programs can provide much deeper analytics for structured data than you can with unstructured but that’s not to say you will have no analytical capabilities with non-structured data.

Emerging tools make it so that unstructured data reacts similarly to structured data, but at much faster speeds with the opportunity to scale quickly. These tools make it possible to analyze sentiments as if they were a black and white piece of data like a ZIP code.

Learn more about how AI is changing NoSQL databases and download BangDB, a NoSQL database that employs machine learning to make unstructured data searchable and usable.

9 Largest Database-as-a-Service (DBaaS) Providers

Today’s IT requires ample storage. But the challenge with today’s storage needs is that they fluctuate. And even companies that have steady database needs require large amounts of storage where managing databases in-house can be time-consuming and expensive.

As a result, most companies look to database-as-a-service providers to fulfill these needs. Databases can serve many purposes but the great benefit of using a DBaaS is that your technology team won’t have to handle the ongoing upkeep and security updates for these databases.

Database rental has many great benefits for consideration when evaluating your needs. For example, some companies use a hybrid model of on-premises databases mixed with managed cloud databases. 

We’ll explain what database-as-a-service is when you should use it, the many benefits you can enjoy from this service, and the top DBaaS providers. 

What is Database-as-a-Service?

The simplest example of what database-as-a-service is that many people understand is Google Drive. Google Drive allocates a set amount of storage to each user. Within the storage, you can create folders and structures to meet your needs.

Likewise, many databases offer structure and processing as part of their storage services. DBaaS encompasses many different services that you likely use every day and think nothing about.

In a sense, website hosting is a database-as-a-service offering a specifically structured database service that renders your website to visitors when they type the URL. 

But there are far larger databases available to meet the needs of businesses and developers. These databases can come in many different types including:

  • NoSQL
  • MySQL
  • PostgreSQL

Different types of databases are more scalable than others. NoSQL is the most modern DBaaS offering options that will grow with your company and applications quickly.

When you purchase a DBaaS subscription, you’ll get all the necessary tools to manage a cloud-based database. These tools include licenses, provisioning, maintenance, and ongoing support.

Cloud-hosted APIs make it possible for developers to create applications in the cloud and write and read data from those cloud-based databases.

DBaaS Benefits

Learn about the benefits of DBaaS and then read about the fastest NoSQL Databases here.

The benefits that a database-as-a-service offers are immense and impactful for most organizations. Here’s a look at these great benefits.

  1. Excellent service quality: to get access to a cloud-based database, you’ll agree to a service level agreement that outlines the performance and support that comes with your subscription. As such, these database companies must meet these high standards and uphold security guidelines. The availability of the database must match what is outlined in the service agreement.
  2. Fast deployments: your in-house resources will no longer have to worry about administrative tasks. Instead, they can focus on innovating for your company and deploying those innovations to aid in business growth instead of focusing on keeping systems running.
  3. Flexibility: as your need for resources changes, it’s easy to upgrade or decrease your database usage. Most DBaaS companies charge based on usage, which means you won’t have to worry about changing licensing agreements or subscription levels from month to month as your needs change.
  4. Quick provisioning: most database-as-a-service providers offer self-service capabilities so that you can get started quickly with just a few clicks. That way, you don’t have to worry about governance or administrative responsibilities.
  5. Improved agility: business requirements can change from one hour to the next. With on-premises solutions, you might need a deployment to address new requirements. But DBaaS allows you to be much more agile to meet changing needs and requirements.
  6. Outstanding security: DBaaS providers handle the security side of things, which means you won’t have to worry about keeping the database updated to protect your valuable data. These providers offer multi-layered security to protect data at rest.

Get Started with BangDB NoSQL Database-as-a-Service

BangDB is a leading NoSQL DBaaS. With artificial intelligence to help you identify and solve relevant problems facing your organization. The database natively supports AI and streaming services to allow you to log events to evaluate patterns in real-time.