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This article mainly explains "what you must know about NoSQL". The content of the explanation is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn what you must know about NoSQL.

Understand why NoSQL was born

1. From persistent data storage to supporting modern applications

To understand why NoSQL was born, I think it is useful to step back and take a quick look at the evolution of data storage solutions.

Between the 1950s and 1970s, early data management systems such as flat files, hierarchical databases and network databases were created. It is good enough for the world's persistent data storage to avoid data loss.

In the 1970s, relational databases were about to solve the problem of data inconsistency. And so powerful that they become the industry standard, enabling individual teams and multiple applications to search, query, and manipulate on a single logically relevant data, resulting in huge productivity benefits.

But the exponential growth of Web applications, e-commerce and social media in the 2000s created new challenges. Technology giants such as Google and Amazon have found that they need to support a large number of users on the web, supporting thousands of business users from a single database application.

Specifically, we now have a new problem: how to consistently store large datasets and support modern applications that continuously process a large number of user requests in discontinuous situations? In the appropriate technical terms, this is the following question:

Support for a large number of reads and writes

Ensure low latency response time

Maintain high availability.

Although this problem with relational database can be solved to some extent, it usually has increased complexity and potentially high cost. As a result, two highly influential NoSQL database examples were born: DynamoDB from Amazon and Bigtable from Google. This marks the explosion of NoSQL databases, and since then, people have never looked back.

Define NoSQL properties

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two。 Is structural atheism.

Architectural atheism, NoSQL databases do not need schema design. This means that 2 is good for relational databases.

First, avoiding a few months of previous architectural design work means shorter development time, which eventually translates into faster web and mobile applications.

Second, architectural atheism gives you the flexibility to change the data structure in the middle of application development (rather than through the dreaded architectural redesign process).

This is important if you are dealing with different data structures. For example, e-commerce applications need to use different product specifications to store different projects. The size, color, shape and brand attributes of fashion products, while microwave ovens may include size, capacity, wattage and manufacturer's warranty details.

3. Non-relation

With NoSQL databases, non-relational data is not forced into rows and columns. Because developers can keep the stored data structures closer to their original form, they can minimize the amount and complexity of the code to store, manage, and search information. This in turn is more manageable for testing, troubleshooting and bug fixing.

In addition, as the data is stored in an informal format, sales orders in the NoSQL database will be saved with all related products and shipping addresses. This translates into simple data storage and retrieval as well as faster queries.

If you think Denormalising data also has its disadvantages, such as redundancy and higher data storage costs. You are absolutely right! At the end of the day, it's a matter of judging that you're willing to pay for faster application development and data queries.

4. Released inherently on commercial hardware

Given that any modern application must be distributed across a variety of commodity servers. This not only meets a large amount of data, but also caters to consumer expectations that are always seamless on websites and applications. They must respond in milliseconds and are always available to many concurrent users whenever needed.

Oracle RAC or SQL Server Alwayson is an example of a distributed relational database. Unfortunately, relational databases must rely on manual fragmentation, which usually leads to greater complexity and operating costs.

In contrast, many NoSQL databases, such as HBase,Riak and Cassandra, are inherently distributed, with built-in options that control how data is replicated and distributed on cheap commodity servers. Even if one of the servers crashes and burns, your data can still be accessed to your application to continue to run and serve user needs. This makes NoSQL databases more suitable for large-scale data storage to support websites and customer-facing applications.

Note: not all NoSQL databases are designed to be distributed or must be distributed. However, when availability and scalability are the most important issues, it makes sense to choose a distributed product.

Select NoSQL database

5. There are many types of NoSQL databases

The four most widely used types of NoSQL databases are keys, documents, column families, and graphic databases. Each purpose is very different.

The key-value database saves the data as a set of key-value pairs. The key serves as a unique identifier for the associated value of the overview. Some examples include Memcached,Voldemort,Redis and Riak.

The document database stores and queries data and JSON-like documents with nested structures. The two main open source options are MongoDB and CouchDB.

Column-oriented databases are designed in such a way that the data of a given column is stored together. Some of the more popular products are HBase,Cassandra,Hypertable.

The strength of graph databases lies in their model network (that is, things connected to other things). It is usually found in social network applications that graphic databases can quickly extract relevant data from horizontal nodes and relationships. You may have heard of its most famous example: Neo4j.

The NoSQL database has a wealth of choices, but none of them are created equally. A wide range of NoSQL products show that one person can Excel Excel in a management document, while another can provide an unparalleled advantage to manage social networks. Here are some real-life use cases for each NoSQL database type.

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6. The business problem that best suits you

When choosing which NoSQL databases to adopt, you must ask yourself that the question is not "can this database store my data?" Instead, "is it the best fit for my business problems and application requirements?"

But it is clear to me that many other decisions that are "best suited" can be difficult because there are so many considerations. Each consideration carries a different weight on the final decision of different use cases.

To provide you with a starting point, here are six key factors that you must consider when determining the best fit for a data storage solution.

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7. There are certain tradeoffs for all kinds of options.

As the database landscape changes faster and we dare to predict, choosing the best choice is very complex.

For example, while graphics databases such as Neo4j will be suitable for social media such as Facebook, the stored pure storage will easily overwhelm any existing graphics database. Therefore, it makes sense to prefer larger-scale options (such as HBase or RIAK), which has nothing to do with social networks in the first place.

The point here is that each NoSQL database should be evaluated as a separate technology, rather than being rigid and transparent based on its classification. Potential trade-offs must be carefully considered because they can be deal-breakers.

To illustrate this point, the following is a simplified comparison of the databases selected from the book over a seven-week period.

Note: in the table, I also include a relational PostgreSQL to highlight the tradeoffs for selecting a relational database on other non-relational peers. In addition, new features can be released to address our claims to address some potential trade-offs, so it's best to check for the latest updates.

Thank you for your reading, the above is the content of "what NoSQL must know". After the study of this article, I believe you have a deeper understanding of what you must know about NoSQL, and the specific use needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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