Popular NoSQL Databases
Overview
In this tutorial, we will learn about popular NoSQL databases. NoSQL, also known as “Not Only SQL”, is a well-known approach to database design. NoSQL databases are not mainly built on relational database tables and do not use SQL to manipulate data. This is where the name NoSQL comes from. However, note that NoSQL was created as a support for SQL, and not as its replacement.
NoSQL databases are distributed databases. The information is stored on different servers and nodes, and these can be remote or local. Due to distributed nature, we can expect the availability and reliability of the data.
NoSQL Databases
Organizations that offer services without latency and process large volumes of data using NoSQL databases. Some of the popular NoSQL databases are as follows:
- Apache Cassandra
- MongoDB
- Google Bigtable
- Amazon DynamoDB
- Apache HBase
- Hive
- Riak
Apache Cassandra
Apache Cassandra is an open-source NoSQL Database that manages massive amounts of data in a fast manner. Apache Cassandra is widely used by many organizations. Cassandra supports multi-datacenter replication. Data replication is automatic across multiple cluster nodes.
Website:: https://cassandra.apache.org/
MongoDB
MongoDB is a developer data platform that provides the tools and services to build distributed applications fast.
Website:: https://www.mongodb.com/
Amazon DynamoDB
Amazon DynamoDB is a fast NoSQL Key-Value Database. It is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale.
Website:: https://aws.amazon.com/dynamodb/
Google Bigtable
Google Bigtable is a cloud NoSQL database service. It is a fully managed, scalable NoSQL database service for large analytical and operational workloads with up to 99.999% availability.
Website:: https://cloud.google.com/bigtable
Apache HBase
Apache HBase is a distributed Hadoop database. It is a scalable big data store.
Website Link:: https://hbase.apache.org/
Hive
Hive is used to analyze large amounts of data on Hadoop. We can manage and query large amounts of data using Hive.
Apache Hive is a distributed, fault-tolerant data warehouse system that enables data analytics on a massive scale. Hive is built on top of Apache Hadoop and supports storage on S3, etc through HDFS. Hive allows users to read, write, and manage petabytes of data using SQL. Hive Metastore(HMS) is a critical component of many data lake architectures. It provides a central repository of metadata that can easily be analyzed to make informed decisions.
Hive supports HQL( Hive Query Language) for modeling and interaction with the database. Hive also supports JDBC API( Java Database Connectivity).
Website Link:: https://hive.apache.org/
Riak
Riak provides NoSQL database solutions for building distributed applications and systems to scale large amounts of unstructured data.
Website Link:: https://riak.com/