The most popular NoSQL Database in 2022: Which one should you pick?
Currently, databases are very important for modern applications such as web, mobile, games, and many more that require databases which is more flexible, reliable, high-performance, and highly functional which provides a great user experience.
In the past few years, NoSQL databases have been gaining a lot of popularity as they are said to be more scalable and flexible.
NoSQL databases are an emerging type of database management system that differs from the traditional relational database management systems.
They became popular in the early 2000s, and by 2022, NoSQL databases will be used by over 88% of companies.
One of the main reasons for their increased popularity is because they can store data in any format (text, numbers, images, videos), which means they are great for handling lots of different types of data. The other reason is that they are often easier to maintain than traditional relational databases.
Why you should use NoSQL Databases?
The most important advantage of using a popular NoSQL database is NoSQL databases are a type of database that doesn’t use tables for storing data.
They are designed to store large volumes of data that are structured in a variety of ways, whereas relational databases require the data to be structured into tables. Their design allows them to handle huge amounts of unstructured data.
Many people wonder what the most popular NoSQL Database will be in 2022. There are many different types so it’s hard to predict which one will be the most popular. Let’s see the top 10 NoSQL Databases and lastly will talk about the most popular ones and the reasons why you should choose them.
Let’s get started
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The Top 10 popular NoSQL Databases in 2022.
MongoDB is an open-source document database that stores data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON).
It has become the most popular NoSQL database in recent years due to its ease of use and rich features. MongoDB was designed for modern data applications that require a collaborative environment where information can be easily shared among a large number of users.
MongoDB has the following features:
- Schemaless: There is no need to define your schema upfront since you can just save any type of content without having to define its structure first.
- Dynamic: The schema will automatically adjust depending on what type of content you save inside it, meaning that you don’t have to define your own structure upfront.
- Automatic partitioning: With MongoDB, there is no need to manually tune the number of partitions or size of each partition for a dataset because it will do this for you automatically depending on how much data you have saved inside the database.
2. Apache Cassandra
Cassandra is a free and open-source distributed database management system designed to handle large amounts of data across many commodity servers with no single point of failure.
Cassandra offers a wide range of features with no need for in-depth knowledge from the user. This makes it a particularly well-suited and the most popular NoSQL database to new users who have limited or no experience managing databases.
It offers two types of storage: row storage and column family storage. Rows are written to disk sequentially on rows within the same partition (or “table”). Column families are sorted by key and stored together on disk.
This allows for more efficient compression than row storage alone. Cassandra can be used in conjunction with Hadoop to increase performance for batch tasks via the use of Cascading – an open-source Java library that provides high-performance pipes between Hadoop MapReduce jobs and real-time operations on Apache Cassandra databases.
3. Apache HBase
Apache HBase is a distributed, scalable, and durable data storage system with a column-oriented architecture. It offers random real-time read/write access to big data sets of any size. HBase can be used as a key-value store, a real-time analytics system, or a hybrid of both.
Apache HBase is built on top of HDFS and MapReduce and supports a similar set of functionality as a relational database such as MySQL or Postgres. Unlike relational databases, Apache HBase can scale up to handle gigabytes or terabytes of data per node rather than managing at the level of scaling out across multiple nodes.
4. Apache CouchDB
Apache CouchDB is a document-oriented database that provides a flexible data model, HTTP-based JSON interface with full CRUD, MVCC for data synchronization, and incremental changes.
CouchDB is built on top of Erlang with Futon as its web-based management interface. It offers easy scaling, even for very large datasets. It is very efficient with disk space usage.
It has a flexible query language that supports ad hoc style queries as well as the ability to create views on the data. CouchDB allows you to store your data in the form of JSON objects, keyed by any variety of string values.
It has been described as a popular NoSQL database, though it differs from other databases classified as NoSQL because it offers conventional ACID transactions with MVCC support.
Neato4j is a graph database that was designed for the modern age. It uses a simple and intuitive query language, making it easy to use. It also has a rich set of features that helps you organize data in a way that makes sense to you.
From visualizing your data as a map to filtering by specific nodes or relationships, there are many ways to explore and present your data with Neo4j.
Neo4j has been used in various industries from web development to cybersecurity to process mining.
RavenDB is an open-source document database that has the power to be used for any type of application data.
RavenDB’s schema-free design makes it possible to store both traditional relational data and semi-structured JSON documents in the same repository. RavenDB is multithreaded which allows for parallel querying, indexing, and replication.
Both RavenDB and MongoDB offer document storage, however, they differ in how they store documents. In RavenDB, data is stored as JSON documents and the queries are sent as JSON; whereas in MongoDB, data is stored as BSON (binary JSON) and queries are sent as BSON.
RavenDB also offers support for more types of relationships: one-to-one, one-to-many, many-to-many; whereas MongoDB only has support for one to many relationships.
Redis is a database that stores data in key-value pairs. It is an open-source in-memory database that was designed to persist on a disk.
The Redis key-value store provides fast access to data that can be either read or updated. It supports data structures other than strings, including hashes, lists, sets, and sorted sets. All its contents are stored in RAM which makes it great for applications where the dataset might get too large for memory or when you need the fastest possible access to the data.
So these are the top 7 popular NoSQL databases that are used to store big data in companies. It’s up to you which database you want to use.
Although all of them are just mind-blowing still developers use MongoDB as the most popular NoSQL database. Why? Let’s see some reasons why you should use the MongoDB database.
5 Reasons why MongoDB will be the most popular NoSQL database in 2022?
NoSQL databases are more popular when it comes to storing big data in companies. There are many reasons for this, the most important being the drastic difference in performance when it comes to queries.
Following are the five reasons why MongoDB will be the most popular NoSQL database in the future.
- It is very easy to use, which makes it a great choice for beginners.
- It is easy to deploy and can be hosted on any infrastructure with any operating system.
- It has an intuitive query language that is very powerful, yet still easy to learn.
- It has built-in horizontal scalability.
- The company supports open source projects and mongodb can be used on open source platforms.
Popular NoSQL databases are non-relational database that is used in a wide range of applications. It doesn’t support the traditional structural hierarchy of relational databases, but instead, it is able to store and retrieve data in various formats. It has been proven to be more reliable, easier to use, and scalable with data volumes increasing over time.
In conclusion, a popular NoSQL database is a cost-effective solution for solving scaling problems associated with relational databases which are difficult to scale vertically or horizontally.
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