Without databases, most software applications would not be possible. Databases are the cornerstone of any type and size of application: web-based for data storage across enterprise-level projects that require large amounts of volume or speed in transferring large chunks over networks; an embedded system where you can find low level interfaces with tight timing requirements unlike anything else compared to real time systems. Of course, we cannot miss Artificial Intelligence, Deep Learning, Machine Learning, Data Science, HPC, Blockchain and IoT, which are totally dependent on data and definitely need a database to store and process it later.
Now, let’s read about some of the essential types of popular databases.
He Oracle: Oracle has provided a robust, enterprise-grade database to its customers for nearly four decades. It remains the most widely used database system, according to DB-Engines, despite strong competition from open source SQL databases and NoSQL databases. It has C, C++ and Java as built-in assembly languages. The most recent edition of this database, 21c, contains a large number of new features. It’s compact, fast, and has many additional features, such as JSON from SQL.
mysql: Web development solutions are the most frequent use of this database. MySQL is a structured query language that is built on C and C++. MySQL’s enterprise-grade functionality and free and flexible community license (GPL), as well as an up-to-date commercial license, made it immediately famous in the industry and community. The key objectives of the database are stability, robustness and maturity. There are several editions of SQL Database, each with its unique set of features.
postgresql: PostgreSQL is the most advanced open source relational database. It is a C-based database management system used by companies that handle large volumes of data. This database management software is used in various gaming applications, database automation tools, and domain registrations.
Microsoft SQL Server: MS SQL is a multi-model database that supports structured data (SQL), semi-structured data (JSON), and spatial data. It is compatible with Windows and Linux operating systems. It was the most popular midrange commercial database on Windows systems for the last three decades. Microsoft SQL Server has undergone considerable improvements and revisions over the years, without being as inventive or advanced as others. It can be very beneficial when the development platform is tightly coupled with other Microsoft products.
MongoDB: The use of object-oriented programming languages to load and retrieve data in RDBMS requires additional mapping at the application level. In 2009, MongoDB was released as the first document database to address those difficulties, particularly document data processing. It is used for semi-structured data where consistency trumps availability.
ibmdb2: DB2 is a multi-model database that supports structured (SQL), semi-structured (JSON), and graph data. It is also a converged database with great OLAP functionality thanks to IBM BLU Acceleration. DB2 LUW was also available for Windows, Linux, and Unix.
redis: It is a well known open source database. Redis can be used as a distributed key-value database that runs in memory. It can also be used as a distributed cache and message broker. It can handle massive amounts of data. Supports many data structures.
cassandra: It is a widely used database with an open, distributed kernel, large columnstore and Apache 2.0 license. This is a scalable database management software that is frequently used by businesses to handle large amounts of data. Its decentralized database (Leaderless) with automatic replication is one of its main advantages, allowing it to become fault tolerant without fail. Cassandra Query Language (CQL) is an easy-to-use, SQL-like query language.
elasticsearch: Released in 2010, Elasticsearch is an open source, distributed, multi-tenant full-text search engine with a REST API. It also supports structured and schema-free (JSON) data, which is ideal for analyzing log and monitoring data. I can handle significant amounts of data.
MariaDB: MariaDB is a relational DBMS that works with the MySQL protocol and clients. The MySQL server can be easily changed with MariaDB without the need to change the code. It is more community driven compared to MySQL. MariaDB’s “ColumnStore” storage engine combines columnar storage with a massively parallel distributed data architecture. Through MaxScale and Spider Engine, it also provides horizontal partitioning. As a result, MariaDB can be used as an OLAP database.
firebirdsql: Firebird is a free SQL relational database management system. It is compatible with Windows, Mac OS X, Linux, and many Unix platforms. This foundational database management system software solution has enhanced the cross-platform RDBMS.
OrientDB: OrientDB is an open source NoSQL multi-model database. It is a database management system that supports graph, document, key-value, and object-oriented database models, improving efficiency, security, and scalability.
DynamoDB: Amazon’s DynamoDB is a non-relational database. It is a fully managed, serverless, key-value NoSQL database built to run high-performance applications at any scale. Built-in security and in-memory caching and constant latency are aspects of this database application.
SQLite: Created in 2000, SQLite is an open source relational database management system with an integrated SQL database. It is a C language library. It is a fantastic database that requires no configuration, server or installation. SQLite is included in all mobile phones and most laptops, and in many other applications that people use every day.
neo4j: Neo4j is an open source Java-based NoSQL graph database. It uses the Cypher query language, which is promoted as the most efficient and expressive way to express queries about relationships. Data is recorded as graphs instead of tables in this database management system software.
References:
- https://towardsdatascience.com/top-10-databases-to-use-in-2021-d7e6a85402ba
- https://appinventiv.com/blog/top-web-app-database-list/
Consultant Intern: Currently in her 3rd year of B.Tech from Indian Institute of Technology (IIT), Goa. She is an ML enthusiast and has a strong interest in Data Science. She is a very good learner and tries to be well versed in the latest advancements in artificial intelligence.
