NoSQL - Scaling Out / Up (2024)

FAQs

Do NoSQL databases scale well? ›

NoSQL databases are horizontally scalable. You can handle higher traffic via a process called sharding, which adds more servers to your NoSQL database. Horizontal scaling has a greater overall capacity than vertical scaling, making NoSQL databases the preferred choice for large and frequently changing data sets.

Basically, if we have to handle higher computing load and we choose to upgrade the hardware, we call it vertical scaling or scaling up. But if we choose to move to a distributed architecture and add more computers to solve our problem we call it horizontal scaling or scaling out.

Some scalable NoSQL databases use a distributed architecture to achieve high scalability and availability. These databases are often designed to be horizontally scalable, meaning that data is partitioned across multiple servers, and new servers can be added to the system to increase capacity as needed.

The nature of horizontal scaling with NoSQL databases means that they can handle extremely large amounts of data—even as the data is growing—in a more efficient way.

The lack of structure can make data untrustworthy and difficult to organize. Common complaints are listed below: The lack of SQL: The consistent complaint about NoSQL is that it doesn't come with SQL. SQL is a mature technology, designed for organizing data, while NoSQL is not.

Lack of standardization - NoSQL databases have no standard query language like SQL and lack standards in data modeling, integrity, etc. This can make applications less portable. Eventual consistency - Most NoSQL systems sacrifice ACID transactions and immediate consistency for performance and partitioning tolerance.

Scaling up vertically means adding more compute resources—such as CPU, memory, and disk capacity—to an application pod. On the other hand, applications can scale out horizontally by adding more replica pods.

NoSQL databases are inherently more scalable than relational databases because you can scale them both vertically and horizontally.

As a service offering, MongoDB Atlas makes scaling as easy as setting the right configuration. Both horizontal and vertical scaling are supported. Vertical scaling is as simple as configuring a cluster tier. Note that even within a tier, further scaling is possible (including auto-scaling from the M10 tier upwards).

In NoSQL databases, data is stored together (not separately, as with SQL). This means that it's faster to perform read or write operations on one data entity compared with SQL databases. Essentially, SQL is great for protecting data validity, whereas NoSQL is ideal for when you need fast availability of big data.

Why is MySQL not scalable? ›

MySQL Scalability Limitations

Today's largest MySQL installations require sharding to scale, which involves splitting a data set over multiple nodes or instances. The third MySQL limitation is that most sharding solutions in MySQL are manual and add complexity to the application code.

To optimize your NoSQL database for high performance and efficiency, you can use techniques such as indexing, caching, compression, aggregation, and batch processing.

NoSQL databases come in a variety of types based on their data model. The main types are document, key-value, wide-column, and graph. They provide flexible schemas and scale easily with large amounts of big data and high user loads.

NoSQL databases are typically designed for distributed use cases, and write-heavy systems can be supported by having multiple write shards for the same data partition (called peer-to-peer replication).

When compared to relational databases, NoSQL databases are often more scalable and provide superior performance. In addition, the flexibility and ease of use of their data models can speed development in comparison to the relational model, especially in the cloud computing environment.

NoSQL Databases Enable Horizontal Scaling (Scaling Out)

This architecture is often referred to as 'horizontal scale,' or 'scaling out' (NoSQL database horizontal scaling). To add capacity to a NoSQL database, administrators simply add more nodes, a very simple process in modern cloud environments.