The database is a collection of information which is organized in such a way that it can be easily accessed, managed and updated. Before you start with the most popular NoSQL databases. You need to know about the NoSQL database.Most of the programmers don’t know what this means. It’s not just SQL. After getting acquainted with the NoSQL database, we’ll jump into the Best NoSQL database for the 2020 year, and we’ll also see Cassandra vs MongoDB vs HBase.


NoSQL databases, also known as non-relational or distributed databases, serve as an alternative to relational databases. They can store and process unstructured data (social media data, photos, MP3 files, etc.) and offer more flexibility and scalability to developers.
Data in non-relational databases can be changed on the fly without affecting any existing data. In addition, NoSQL databases can be run across multiple servers, so scaling them is cheaper and easier than scaling SQL databases.

And since NoSQL databases don’t rely on a single server, they are more fault-tolerant. This means that if one component fails, the database may continue to operate.But NoSQL databases are less mature than SQL databases, and the NoSQL community is not as well defined. Furthermore, the NoSQL databases often sacrifice ACID compliance for availability and flexibility.

NoSQL Database Properties

NoSQL is a schema-less alternative to SQL and RDBMS designed to store, process and analyze extremely large amounts of unstructured data.

The principles of ACID (atomicity, consistency, isolation and durability) are reduced in NoSQL databases. In addition, the standardization process in NoSQL is not mandatory.Due to the size and speed of modern data, it is preferable to de-normalize NoSQL databases.

The databases of NoSQL have the following properties:
  • They have higher scalability.
  • They use  distributed computing.
  • They are cost-effective.
  • They support a flexible schema.
  • They can process both unstructured and semi-structured data.
  • There are no complex relationships, such as those between tables in the RDBMS.
Five NoSQL Database Programmers should learn in 2020.

As there are many NoSQL databases available on the market, such as Apache Cassandra, MongoDB, Redis, and Couchbase, but each has some special features and there are pros and cons of using them. Good knowledge of these is required to make informed decisions on the basis of your requirements.

1. MongoDB

MongoDB is an object-oriented, simple, dynamic, scalable NoSQL database. It is based on the NoSQL document storage model. Data objects are stored as separate documents inside the collection instead of being stored in the columns and rows of the traditional relational database. MongoDB uses schema-like JSON documents.

  • Provides high performance
  • Auto-sharding
  • Run over multiple servers
  • Supports Master-Slave replication
  • Data is stored in the form of documents of the JSON style
  • index any field in a document
  • It has an automatic load balancing configuration because of the data stored in the shards
  • Supports regular expression searches
  • Easy to administer in the case of failures


  • Easy to setup MongoDB
  • MongoDB Inc. provides professional support to its clients
  • Support ad-hoc query
  • High-Speed Database
  • Schema-less database
  • Horizontally scalable database
  • Performance is very high


  • Doesn’t support joins
  • Data Size is High
  • Nesting of documents is limited
  • Increase unnecessary usage of memory
2. Apache Cassandra 

Apache Cassandra is a free and open source NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.

The Apache Cassandra database is the right choice if you need scalability and high availability without compromising performance. Linear scalability and proven fault tolerance for commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data.

  • Linearly scalable
  • Maintains a quick response time
  • Supports properties such as Atomicity, Consistency, Isolation and Durability (ACID)
  • Supports MapReduce with Apache Hadoop
  • Maximal flexibility to distribute the data
  • Highly scalable
  • Peer-to-peer architecture
PROS OF apache cassandra

  • Highly scalable
  • No single point of failure
  • Multi-DC Replication
  • Integrate tightly with other JVM based applications
  • More suitable for multiple data-center deployments, redundancy, failover and disaster recovery
  • Limited support for aggregations
  • Unpredictable Performance
  • Doesn’t Support ad-hoc query

Redis (Remote Dictionary Server) is a key-value store. It is an open-source in-memory database project that implements a distributed, in-memory key-value store with optional durability. It can also be used as a cache and as a message broker.

Supports data structures such as strings, hashes, lists, sets, sorted range query sets, bitmaps, hyper logs, and radius query geospatial indexes.
  • Automatic failover
  • Holds its database entirely in the memory
  • Transactions
  • Lua scripting
  • Replicate data to any number of slaves
  • Keys with a limited time-to-live
  • LRU eviction of keys
  • Supports Publish/Subscribe
PROS OF redis
  • Supports a huge variety of data types
  • Easy to install
  • Very fast (perform approximately 110000 SETs per second, approximately 81000 GETs per second)
  • Operations are atomic
  • Multi-utility tool(used in a number of use cases)
  • Redis sentinel is featured provided by Redis to create replication into a distributed system
CONS OF redis
  • Doesn’t support joins
  • Knowledge required of Lua for stored procedures
  • The data set must fit comfortably into the memory

4. Apache HBase

HBase is an open-source, non-relational, distributed database modeled after Google’s Bigtable, written in Java. It is developed as part of Apache Software Foundation’s Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System), providing Hadoop’s Bigtable-like capabilities.

  • Support automatic failure
  • Linearly scalable
  • Provides data replication
  • It integrates with Hadoop, both as a source and as a destination
prOS OF Hbase
  • Provides fast lookups for larger tables.
  • Provides low latency access to single rows of billions of records
  • Easy Java API for client
  • Auto-sharding
  • License-free
  • Handle large datasets on top of HDFS file storage
  • Flexible on schema design
  • High-speed
  • Doesn’t support transaction
  • No permissions or built-in authentication
  • Indexed and sorted only on key.
  • Single failure point (when only one HMaster is used)
  • Doesn’t support for SQL structure
  • Memory issues on the cluster


The focus is on the ease of use of the web. It’s a database of NoSQL document stores. Couchbase Server is a database of NoSQL documents for interactive web applications. It has a flexible data model, is easily scalable and consistently delivers high performance. Couchbase Server, JSON documents are used to represent application objects and the relationship between objects.


  • Index partitioning
  • Support JSON data natively via N1QL queries
  • Data Compression
  • Couchbase Eventing Service
  • proS OF couchbase

    • Aggregate optimization
    • Reduces network, memory, and storage costs.
    •  Great admin panel that gives tons of insights into how your cluster performs.


    • Couchbase is not open source

Thank You!

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