Ever wondered how companies like Amazon or Netflix deal with data of millions of users at one instance? They create personalized experiences by using top NoSQL databases that are ideal for handling large volumes of unstructured data. Web development added with top NoSQL databases help companies enhance application performance along with effective data analytics
But why do NoSQL databases bear such an important role in big data?
Today, NoSQL databases are not just a fad but have become part of the imperative. Research is testimony to their effectiveness in managing data in these modern days, and their global market is growing upwards of 30% annually.
In this post, we will discuss 11 top NoSQL databases that are changing the way we think about big data. Whether you’re a tech enthusiast or a business executive, the developments within these tools are sure to improve your data strategy and give you a competitive advantage.
Understanding NoSQL Databases: Why It Should Matter to You?
NoSQL databases-abbreviated for “not only SQL”-don’t use the traditional rows and columns of relational databases.. Instead, they offer a flexible way to store and retrieve data.
Think of it this way:
A growing online store can benefit from top NoSQL databases. As customers, products, and interactions grow, NoSQL handles the extra data easily. It stays fast and doesn’t slow down like older systems might.
Here’s another example: Imagine a coffee shop. A traditional database (SQL) is like a fixed menu with standard coffee sizes and flavors. It works well for regular orders but struggles with custom requests like “half-caf, oat milk latte with hazelnut syrup.”
NoSQL is like a system built for custom orders. It’s flexible, adapts quickly, and handles a wide range of requests with ease.
If your business has a mobile app, NoSQL can store all kinds of data—user profiles, reviews, and even photos. Unlike SQL, it adjusts to new needs without expensive updates.
But Why does this matter?
If your data changes fast or your user base is huge, NoSQL is the way to go. It works well for complex data, like social media interactions, and grows with your business. Whether a small startup or big company, understanding NoSQL helps you stay innovative and scale faster.
What would be the 11 top NoSQL databases used in big data solutioning?
In today’s date, data is everywhere. Handling big-sized data of various formats often becomes tricky. Here comes the role of top NoSQL databases. Each of these databases is designed for efficient handling of big data, enhancing the performance of web and mobile app development, and meeting peculiar business requirements. Now, we shall explain each of the 11top NoSQL databases that you can use for big data solutions.
MongoDB
MongoDB Representation MongoDB is one of a new generation of databases called NoSQL databases. In fact, over 25,000 companies in over 100 different countries use MongoDB for their database applications. Why? Because MongoDB is flexible. MongoDB stores information in JSON-like forms and therefore is easily changed. It is also very scalable-in that you can simply add servers if your data begins to grow. By the year 2023, MongoDB accounted for approximately 32% of the NoSQL database market.
Apache Cassandra
Apache Cassandra is designed to be reliable and scalable. It’s well-suited for industries where you can’t afford downtime, such as those involving live streaming or electronic commerce. Even under extremely heavy loads, Cassandra can handle upwards of 1 million writes per second.
For instance, Netflix and eBay rely on Cassandra to store and analyze data in real time.
Redis
Redis is an in-memory database, meaning all of your data is stored in memory instead of on disk. This makes it extremely fast.
It’s pretty commonly used for storing caches and user sessions. In 2024, it hit over 1.8 million operations per second and remains one of the most beloved solutions for applications that need responses fast.
Couchbase
Couchbase combines the best of NoSQL with SQL. It provides for flexible data models and runs at high speeds, managing more than 100,000 transactions per second. Developers who know SQL will find Couchbase easy since it has SQL-like querying. This makes it perfect for apps like online stores.
Amazon DynamoDB
DynamoDB is a fully managed AWS service that allows for highly scalable databases. It automatically adjusts the capacity based on an application’s workload, wherein the throughput can handle up to 20 million requests per second. Thus, it is highly effective in businesses where sudden surges of traffic occur, like during sales or major product launches.
Neo4j
Neo4j is a graph database; therefore, it is excellent for handling the relationship between data. Could thus be very useful for a wide variety of uses with regards to social networks and recommendation systems. More than 6,000 companies use Neo4j, thanks to the ability of Neo4j to query complex information fast. During the year 2024 alone, it handled over 100,000 queries per second.
Apache HBase
Big data for Apache HBase is built in real time and works well with Hadoop. It’s great for time series and can store massive datasets. HBase offers 2-second low read/write latencies, which are very important in some lines of action, such as finance and telecommunication.
Cosmos DB
Microsoft Azure provides Cosmos DB, which is a globally distributed database. It promises as high as 99.999% availability in uptimes and multi-region data replication. It handled over 1 million transactions per second in 2023 alone and is ideal for enterprise use.
ArangoDB
ArangoDB differs from other databases because it supports multi-model features like graphs, documents, and key-value data. This kind of flexibility for handling different types of data is received quite well by their users. It is capable of processing over 1 million queries per second and hence is considered leading the race between NoSQL solutions.
OrientDB
It supports both graph and document data. It’s also ACID-compliant, meaning it ensures safe and reliable transactions. OrientDB can handle more than 100,000 document inserts per second, making it a solid choice for high-performance apps.
TiDB
TiDB is a database intended for both transactional and analytic processing. It easily scales out, serving millions of concurrent transactions. The unique design of TiDB is improving transaction speed at all levels, making it well liked by businesses that include several complex data needs.
What are some of the data models used by NoSQL databases?
NoSQL databases have been built to deal with modern, fast, and highly scalable applications. They can also adapt to various data models, which include document stores, key-value stores, column-family stores, graph databases, and multi-model databases. Now let’s look at each in turn.
Document Stores
Document stores store data in JSON-like documents. In this format, data is easy to work with and modify. If, for example, one develops a mobile application, databases like MongoDB or Couchbase are great options to take up. They will allow you to store such information as user profiles, settings, and preferences. Because of their powerful search features, one will get to know data in a very fast pace to analyze it for improvements.
Key-Value Stores
Key-value stores manage data in pairs, which allows for very fast data retrieval. For applications that require caching or session management of web applications, Redis or Amazon DynamoDB works quite nicely. You can store temporary information in them, such as items in a shopping cart or user login details. This will keep your application responsive, even under high loads.
Column-Family Stores
Column-family stores organize data by columns, not rows. This structure helps with speed and uptime. Apache Cassandra is a popular choice for apps that need to stay online all the time, like chat platforms or IoT systems. You can use it to save data from sensors or event logs while keeping everything accessible in real time.
Graph Databases
Graph databases are designed to handle relationships between data. For example, Neo4j is perfect for social media apps or recommendation systems. You can map connections between users or suggest products based on their relationships. This makes the user experience more engaging and personalized.
Multi-Model Databases
Multi-model databases combine different types of data models. One example is ArangoDB. It supports many use cases, such as e-commerce or analyzing financial data. By using one database for multiple purposes, you can save time, cut costs, and make scaling your app easier.
Each NoSQL data model has its strengths. Picking the right one is key to making your project successful.
What are some of the Benefits of NoSQL Databases over SQL Databases?
NoSQL databases are changing the way we handle data. They offer many advantages over traditional SQL databases. These include better scalability, more flexibility, faster performance, and lower costs. Here’s how NoSQL databases stand out, especially for managing big data.
Scalability
One big benefit of NoSQL databases is scalability. They can grow easily by adding more servers as your data increases. Unlike SQL databases, which often need expensive upgrades, NoSQL can handle more data without slowing down. In fact, 90% of businesses using NoSQL report better scalability compared to SQL. This means NoSQL is perfect for growing data needs.
Flexibility
NoSQL databases are also very flexible. They don’t need a fixed schema, so you can change data structures quickly and easily. This is great for projects where data needs change a lot, like mobile apps or websites. About 80% of developers say this flexibility helps them work faster. It lets teams focus on building applications without worrying about complex database changes.
Performance
NoSQL databases are designed for specific types of data, so they are really fast. Performing some tasks, such as high reads and writes, NoSQL can run up to 1,000 times faster than SQL in some cases. This speed is very important to those businesses that rely on real-time data, say, analytics or streaming platforms.
Cost-Effectiveness
NoSQL databases are also somewhat cheaper to operate. Many are open-source, meaning there are basically no high licensing fees. With NoSQL, businesses can save money while still getting good performance-even in high loads-which makes NoSQL the intelligent choice for companies trying to cut costs while handling bulky amounts of data.
With all these benefits, NoSQL databases are quickly becoming a top choice for data-driven industries. They offer the tools and flexibility needed to keep up with modern data demands.
What to Consider When Choosing a NoSQL Database
NoSQL databases are gaining momentum due to their flexibility and the ability to scale up according to your needs. But how would you decide which one to use? Choosing the best NoSQL database for your big data solution involves several key factors.
Cost
First, think about the cost of using a NoSQL database. Training your team to use it can be expensive. On average, training costs range from $1,200 to $2,500 per person. If you decide to hire experts instead, that can also raise your budget since skilled NoSQL professionals are in high demand.
ACID Properties
Next, check if your application needs ACID properties. ACID stands for Atomicity, Consistency, Isolation, and Durability. These ensure data accuracy and reliability. Many businesses—about 70%—need strict ACID rules to keep their data safe and correct. If your app depends on these features, a traditional SQL database might be a better option.
Scalability
Scalability is another key point. NoSQL databases are great at scaling up or out. This makes them perfect for handling large data growth or sudden spikes in usage. The NoSQL market is growing fast. Experts say it will reach $141.62 billion by 2033, growing at 31.2% each year. If your app needs to handle big or unpredictable data loads, a NoSQL database is a smart choice.
Savings
Switching to a NoSQL database can also save you money. Studies show that businesses reduce costs by about 30% when they switch to NoSQL. This happens because NoSQL databases often need less hardware and are easier to maintain. Lower training, setup, and management costs can make a big difference too.
High Availability vs. Reliability
Now think about what matters more: uptime or data consistency. NoSQL databases are built for high availability. They can achieve 99.99% uptime thanks to their distributed design. But if your application needs perfect and consistent data, SQL databases might still be the better choice.
Conclusion:
With big data, the selection of the right database becomes a critical point. If you want to work with a modern system that will be scalable, flexible, and fast, you may explore the top NoSQL databases.
At Linkitsoft, we solve big data challenges with advanced NoSQL databases. These tools power applications that are scalable, adaptable, and high-performing. Whether you need a web app, a mobile app, or a data platform, we match the best database to your needs.
Our team understands the strengths of NoSQL databases. We design tailored solutions to handle all types of data: structured, semi-structured, or unstructured. By combining experience and innovation, we create powerful systems built for the future.
