Main databases for artificial intelligence, IoT, deep learning, machine learning, data science and other software applications
Without databases, most software applications would not be possible. Databases are the backbone of all types and sizes of applications: web-based ones for storing data through enterprise-level projects that require high volumes or transfer speed big chunks on the networks; an embedded system where you can find low-level interfaces with tight timing requirements like nothing else compared to real-time systems. Of course, we can’t 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 them later.
Now, let’s read about some of the essential types of popular databases.
the Oracle: Oracle has been providing customers with a robust, enterprise-grade database for nearly four decades. It’s still 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 host of new features. It is compact, fast and has many additional features, such as SQL’s JSON.
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-level features and its free and flexible community license (GPL), as well as an updated commercial license, made it immediately famous in the industry and the community. The main objectives of the database are stability, robustness and maturity. There are several editions of SQL Database, each with its unique set of features.
PostgreSQLName: PostgreSQL is the most advanced open source relational database. It is a C-based database management system used by companies that deal with large volumes of data. This database administration 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 supported by Windows and Linux operating systems. It was the most popular mid-range commercial database on Windows systems for the past three decades. Microsoft SQL Server has undergone considerable improvements and revisions over the years without being as inventive or advanced as others. This 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 in RDBMS requires additional mapping at the application level. In 2009, MongoDB was released as the first document database to solve these difficulties, especially 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 excellent OLAP functionality thanks to IBM BLU Acceleration. DB2 LUW was also available for Windows, Linux and Unix.
Say it again: 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 massive amounts of data. It supports many data structures.
Cassandra: This is a widely used database with an open, distributed kernel, an extensive column store, and an Apache 2.0 license. It is a scalable database management software frequently used in enterprises to manage large amounts of data. Its decentralized database (Leaderless) with automatic replication is one of its main advantages, allowing it to become fault-tolerant without failure. Cassandra Query Language (CQL) is a user-friendly, SQL-like query language.
Elastic search: Launched in 2010, Elasticsearch is an open-source, distributed, multi-tenant full-text search engine with a REST API. It also supports structured and schemaless data (JSON), which is ideal for analyzing logging and monitoring data. I can handle large amounts of data.
MariaDB: MariaDB is a relational DBMS that works with 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 a massively parallel distributed data architecture. Thanks to its MaxScale and Spider engine, it also provides horizontal partitioning. Therefore, 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-, 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 designed to run high-performance applications at any scale. Built-in security and in-memory caching, as well as constant latency are all aspects of this database application.
SQLiteName: 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 does not require any configuration, server or installation. SQLite is included in all mobile phones and most laptops, as well as a host of 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 promotes itself as the most efficient and expressive way to express relationship queries. Data is saved as graphs rather than tables in this database management system software.