The best databases for AI, IoT, deep learning, machine learning, data science and other software applications

The best databases for AI, IoT, deep learning, machine learning, data science and other software applications

Without databases, most software applications would not be possible. Databases are the cornerstone of all types and sizes of applications: web-based ones for archiving data across enterprise-level projects that require high volumes or speed in transferring large blocks across networks; an integrated system where low-level interfaces with tight timing requirements can be found, unlike anything other than real-time systems. Obviously Artificial Intelligence, Deep Learning, Machine Learning, Data Science, HPC, Blockchain and IoT cannot be missing, which are totally based on data and certainly need a database to store and process them later.

Now, let’s read about some of the essential types of popular databases.

THE Oracle: Oracle has been offering its customers a robust enterprise-grade database for nearly four decades. It is still the most used database system, according to DB-Engines, despite stiff 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 number of new features. It’s compact, fast, and has lots of extra features, like JSON from SQL.

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MySQL: Web development solutions are the most popular use of this database. MySQL is a structured query language built in 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 instantly popular 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 own 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 manage large volumes of data. This database administration software is used in various gaming apps, database automation tools and domain registrars.

Microsoft SQL Server: MS SQL is a multi-model database that supports structured data (SQL), semi-structured data (JSON) and spatial data. It is supported by Windows and Linux operating systems. It has been the most popular mid-range commercial database on Windows systems for the past three decades. Microsoft SQL Server has gone through many improvements and overhauls over the years while not being as inventive or advanced as others. It can be very beneficial when the development platform is tightly coupled with other Microsoft products.

MongoDB: Using object-oriented programming languages ​​to load and retrieve data into RDBMS requires additional mapping at the application layer. In 2009, MongoDB was released as the first document database to address these challenges, especially document data processing. It is used for semi-structured data where consistency prevails over 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 capabilities 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 message broker and distributed cache. It can handle huge amounts of data. It supports many data structures.

Cassandra: It is a widely used database with an open core, distributed, extensive column archive and Apache 2.0 license. This is a scalable database management software that is frequently used in enterprises to manage large amounts of data. Its decentralized (Leaderless) database with automatic replication is one of its main advantages, allowing it to become fault tolerant without errors. Cassandra Query Language (CQL) is an intuitive, SQL-like query language.

Elastic search: 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 are ideal for analyzing logging and monitoring data. I can handle significant amounts of data.

MariaDB: MariaDB is a relational DBMS that works with the MySQL protocol and clients. MySQL server can be easily modified with MariaDB without requiring any code changes. It is more community oriented than MySQL. MariaDB’s “ColumnStore” storage engine combines columnar storage with 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 supported by Windows, Mac OS X, Linux and many Unix platforms. This foundational database management system software solution has enhanced cross-platform RDBMS.

OrientDB: OrientDB is an open source NoSQL multi-model database. It is a database management system that supports graph-based, document-based, 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, caching, and consistent latency are all aspects of this database application.

sqlite: Created in 2000, SQLite is an open source relational database management system with an integrated SQL database. It’s a C language library. It’s a fantastic database that requires no configuration, server or installation. SQLite is included in all mobile phones and most laptops and a number of other applications that people use on a daily basis.

neo4j: Neo4j is an open source Java-based NoSQL graphical database. It employs the Cypher query language, which is presented as the most efficient and expressive way to express relationship queries. Data is recorded as graphs instead of tables in this database management system software.



Intern Consultant: Currently in 3rd year of B.Tech at Indian Institute of Technology (IIT), Goa. She is an ML enthusiast and has a keen interest in data science. She is a good student and tries to be well versed with the latest developments in Artificial Intelligence.

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