Industry Analysis

The 10 Most Popular Database
Management Systems in 2024

A Ranking of the Top 10 DBMS According to Developers

Updated: July 25th, 2024.

In July 2024, Stack Overflow published its new yearly Developer Survey ranking of the 10 most popular database management systems (DBMS).

Top 3 DBMS for Developers

The top ranked DBMS remained almost the same, with PostgreSQL once again taking the first place as the most popular database management system for professional developers, followed by MySQL and SQLite, with second and third place respectively. Microsoft SQL Server is still the fourth most popular DBMS, almost reaching third place. The only change in 2024 is Oracle moving to number 9, pushing DynamoDB to 10th place. Shown below are the 10 most popular database management systems among developers:

Top 10 DBMS for Developers

What is a database management system (DBMS)?

A database management system, or DBMS, is a software system used to create and manage databases, allowing end users to create, protect, read, update, delete, retrieve, and execute queries on data. The database management system provides an interface between end users or applications and the databases, making it possible to access, organize, and extract data. Furthermore, administrators can improve data security and integrity when managing databases with database management software.

Multiple types of DBMSs have been developed over the past decades, resulting in diverse types and models available today, such as hierarchical, network, relational, NoSQL, distributed, object-oriented, object-relational, cloud, real-time, and multi-model, which support more than one model to provide more flexibility when working with data.

Hierarchical Database Management Systems

Hierarchical Database Management Systems are used to manage data that is structured in a tree-like form. In this sense, hierarchical databases store data as a parent-child relationship, either top-down or bottom-up. Data are saved as records; the first record is called the root record, and each child record can only have one parent. On the other hand, parent records can have one or more child records.

One of the advantages of using a hierarchical model is how easy it is to add and remove data since the relationships between records have been previously established. This database model was developed by IBM in the 1960s. It was called the Information Management System (IMS) and can be considered the oldest database management system. Other examples are Microsoft's Windows Registry and the XML data storage, which both use the hierarchical structure.

Network Database Management Systems

The network database management system, also known as the CODASYL model, is a DBMS based on a network data model where a record can be related to numerous primary and secondary records. It was developed to solve the limitations of the previous hierarchical DBMS.

In the network DBMS, unlike the hierarchical model, each child record can have multiple parents, making it possible to create more complex relationships. Using a network DBMS, many-to-many relationships are created between entities with a network structure. Data entities are organized into a graph structure which can be accessed through paths. This model is utilized mainly on digital computers.

This database model was widely popular during the 1970s, before being widely replaced by the relational model during the 1980s.

Relational Database Management Systems

A relational database management system (RDBMS), also known as SQL DBMS, is used to maintain relational databases, providing an interface with administrative functions which allow the identification and accessing of relational data.

In relational databases, data is typically stored in tables of rows and columns so that it can be used in relation to another piece of data. Here, primary or foreign keys are used to join multiple tables and ultimately show the relationships that exist between them. Data Analysts then use SQL queries to gain access to insights that allow enterprises to identify new opportunities, streamline their processes, and improve performance. It is the most widely used data model because of its easy-to-understand interface. It is important to note that most RDBMS use SQL to access the database and must store data in a structured form to stay compatible with SQL.

Examples of relational database management software include Microsoft SQL Database, Amazon RedShift, IBM Db2, Google BigQuery, Oracle Database, MongoDB, Couchbase, MariaDB, Microsoft Azure Synapse Analytics, Firebird, Sybase, and more. KingswaySoft offers sophisticated solutions that facilitate data integration with relational DBMSs.

NoSQL Database Management Systems

NoSQL databases are non-tabular databases that store information in a semi-structured or unstructured manner, unlike structured relational tables. As mentioned before, relational databases are SQL-based databases; on the other hand, NoSQL databases are non-relational and generally distributed systems. They are also known as Not only SQL to emphasize that they may provide support for SQL-like query languages.

As storage costs decreased during the 2000s, developers became the main cost of software development. This resulted in the creation of developer productivity-focused databases, such as NoSQL DBMS. Currently, there are five major types of NoSQL databases: key-value, wide-column, graph, in-memory, and document databases, each one with its own data model, advantages, and drawbacks.

Many companies are motivated to implement NoSQL database management systems because of their flexible schemas, as there are no defined schemes. Also, its simple horizontal scalability for big data storage and user loads lets you add as many servers as needed to enhance the capacity of your servers.

Examples of NoSQL DBMS include Amazon DynamoDB, Apache Cassandra, MongoDB, Azure Table, Cosmos DB, Redis, Couchbase, Elasticsearch, and more. KingswaySoft offers robust solutions that facilitate data integration with NoSQL databases and more.

Distributed Database Management Systems

A distributed database management system (DDBMS) is a collection of distributed databases, which could be in different parts of the world, unified as a single system as if they were all stored in one location. In this way, they differ from centralized database management systems, which store data in a single location. To achieve this, the DDBMS synchronizes data periodically to guarantee that data changes are up to date in the centralized database system. The need for companies to share data across multiple units in a timely manner encourages the adoption of this data model. When accessing the data across the distributed databases, this distribution is transparent to the users, meaning they are not aware of the location of the data.

Examples of distributed database management software include Apache Cassandra, MongoDB, Couchbase, and Elasticsearch. Using KingswaySoft software, developers can easily integrate any application or data source with these DBMSs, and many more.

Object-oriented Database Management Systems

Object-oriented database management systems, or OODBMS, are database management systems in which data are represented in the form of objects, which differ from the previously discussed relational DBMS, which use tables instead. Because of this, the object data model does not map to relational rows and columns, storing complex data directly with all its properties and relationships.

This system merges the capabilities of databases and object-oriented programming languages. As network database systems, objects can have many-to-many relationships accessed through pointers. Some industries where OODBMSs have been popular are telecommunications and engineering.

Examples of object-oriented database management system software include MongoDB and Db2. KingswaySoft provides sophisticated connectors that facilitate data integration with OODBMSs and any other application or data source.

Object-Relational Database Management Systems

Object-relational DBMSs (ORDBMS) were created to close the gap and use the advantages presented by both relational and object-oriented data models. They are a mixture of both systems, meaning that ORDBMSs support data types, tabular structures, methods, and are able to store data in rows and tables, like pure relational DMBSs, while also support objects, classes, and inheritance, like object-oriented DBMSs.

This database system could be considered the earliest example of a multi-model DBMS, which we will discuss below.

Examples of Object-Relational DBMS include PostgreSQL, Microsoft SQL Server, and Oracle Database. Using KingswaySoft solutions, businesses can easily integrate these DBMSs with virtually any application or other database system.

Multi-Model Database Management Systems

A multi-model database is a DBMS able to support more than one data model. During the last decades, database management systems were designed with a single data model, which determined how data storage, organization, and manipulation worked.

Today there is a trend toward a multi-model database system, where the user is not constrained to one database model and has more flexibility when working with data. Some database models supported by multi-model database management systems are relational, document, and wide-column databases.

Examples of multi-model database management system software include MySQL, Redis, Oracle Database, Cosmos DB, PostgreSQL, Microsoft Azure SQL Database, Couchbase, Elasticsearch, and more. Using KingswaySoft software solutions, developers can easily achieve bidirectional integration with these DBMSs.

Cloud Database Management Systems

A cloud database management system is a distributed database that is implemented on the premises of a hardware service provider and supplied as a cloud service software system. This way, the user doesn't need to have the network operating system and hardware on-premises and can outsource the database system as a service from a provider. Data is stored and managed in the cloud and can be accessed from any location over a network. This type of database system is highly scalable and attractive for businesses that don't need on-premises network infrastructure. The service cost will depend on the services and storage needs of the renter.

Multi-cloud services are also available through some cloud DBMS. This system makes it possible for businesses to use a mixed cloud environment that is cost-effective and better secured by keeping sensitive data in a private cloud, while regular data in lower-cost public cloud networks.

Examples of cloud DBMS include Microsoft SQL Database, Amazon RedShift, IBM Db2, Google BigQuery, Oracle Database, MongoDB, MariaDB, Azure Synapse Analytics, and more. KingswaySoft offers powerful solutions that facilitate data integration with these cloud database systems.

Real-Time Database Management Systems

Real-time database management systems use real-time processing to manage constantly changing data. This database system stores and processes data in actual time, right after it is generated. These are different from traditional databases that contain persistent data, typically not influenced by time. Real-time data processing needs to be fast enough for results to show right away.

Some industries that rely on real-time are digital libraries, reservation systems, and the stock market system, where there are very rapid and dynamic changes.

In addition to the database management systems mentioned above, there are more available such as spatial/geospatial DBMS, flat-file DBMS, content stores, multivalue DBMS, navigational DBMS, search engines, native XML DBMS, RDF (triple) stores, event stores, and time series DBMS.

The 10 Most Popular DBMS for Developers in 2024

  1. PostgreSQL

    PostgreSQL takes once again the number one spot as the current most popular DBMS for professional developers. It is a cross-platform, object-relational database system (ORDBMS) with over 30 years of development, providing support for SQL (relational) and JSON (non-relational) querying. PostgreSQL is primarily a relational database management system (RDBMS) with object-oriented features, including support for object programming languages, objects, classes, and inheritance. It can also be classified as a multi-model DBMS because it supports more than one data model, such as relational, object-oriented, document, and geospatial databases. Furthermore, it is ACID-compliant and allows extending data types with custom data types, making it very flexible when integrating complex data model tasks with a database.

    It is not surprising that PostgreSQL has taken the number one spot as the preferred DBMS for professional developers. There are many reasons for PostgreSQL's popularity, such as its rich feature-set, powerful add-ons, support for relational and non-relational queries, high SQL standards compliance, extensibility, proven track record, and community support. Also, it is free and open-source, so the source code is available for anyone to edit and customize to fit the project's needs. Big names in the data industry, such as Google Cloud, AWS, and Microsoft, have directed their attention to PostgreSQL's trending potential and created fully managed databases designed to be compatible with it, such as Amazon's Aurora, Google Cloud's AlloyDB, and Microsoft's Azure Database for PostgreSQL.

    PostgreSQL can be easily integrated with any other application or data source by using KingswaySoft's PostgreSQL Connection Manager, Command Task, Source, and Destination components found within the SSIS Productivity Pack. These components empower developers and enable them to work efficiently with complex relational data structures within SSIS. Read more on how to easily streamline your PostgreSQL data integration in the Data Warehousing documentation section.

  2. MySQL

    MySQL also took second place in this 2024 ranking, barely below PostgreSQL. As one of the most popular DBMS, it powers several world-famous applications, such as YouTube, Flickr, Facebook, Twitter, Netflix, and Airbnb. Some of the reasons behind MySQL's high demand include reliability, scalability, performance, high availability, security, and flexibility.

    MySQL is a widely-used open-source relational database management system based on the Structured Query Language, as the name implies. It relationally organizes and stores data in tables, columns, and rows. However, as multi-model databases are the trend in the industry, MySQL also supports other data models, such as document stores and spatial DBMS, and can be deployed in the cloud. MySQL offers a free, open-source license and commercial editions, including MySQL Standard Edition, MySQL Enterprise Edition, and MySQL Cluster CGE. When Oracle Corporation acquired MySQL, the project was forked by its creator, Michael Widenius, to create MariaDB, which we will discuss below.

    MySQL can be effortlessly integrated with virtually any other application or database software system by using the Premium ADO.NET components found in KingswaySoft's SSIS Productivity Pack. These premium components provide expanded functionality allowing developers to easily work with complex relational data structures within SSIS. Read more on how to facilitate MySQL data integration with your business applications in the Premium Data Flow Components documentation section.

  3. SQLite

    SQLite is a stable C-library that implements a transactional SQL (relational) database engine which stores all data in a single physical file. It differs from other relational systems, such as MySQL and PostgreSQL, because SQLite is serverless (no client-server architecture). Because of this simplicity and its small and self-contained design, this program gets embedded into many popular applications, operating systems, web browsers, and mobile phones. SQLite is fast, cross-platform, ACID-compliant, and zero-configuration, meaning it does not require any setup or administration. Also, as free, open-source software, the source code is in the public domain and available for anyone to read and customize.

    Easily integrate SQLite with any other application or data source by using the Premium ADO.NET components within KingswaySoft's SSIS Productivity Pack. These components enable developers to facilitate SQLite integration with any other application or data source. Read more on how to easily integrate SQLite data in the Premium Data Flow Components documentation section.

  4. Microsoft SQL Server

    Microsoft SQL Server is a relational database management system developed and sold by Microsoft Corporation. As a database server, its primary function is to store and retrieve data requested by other applications, which may be on-premises or over a network connection. Data retrieval from SQL Server databases is achieved through queries, expressed using the T-SQL (Transact-SQL) language, which is a variant of SQL. This is then processed by the query processor, which decides which steps are necessary to retrieve the data in the shortest time through query optimization.

    There are numerous editions of Microsoft SQL Server, each tailored towards a particular audience with different needs and budgets. The first version of Microsoft SQL Server was released in 1989, and to this day, the name of the software product has not changed. Its name is descriptive, meaning a server built on top of standard programming language (SQL). SQL Server also offers several add-on services, such as machine learning, replication (transaction, merge, and snapshot), analysis, reporting, notification, integration (data import, data integration, and data warehousing), full text search, SQLCMD, Visual Studio, SQL Server Management Studio, Azure Data Studio, and Business Intelligence Development Studio.

    Easily integrate Microsoft SQL Server with any other application or data source by using the Premium ADO.NET components within KingswaySoft's SSIS Productivity Pack. These components put more power in the developer's hands and make SQL Server integration easy. Read more on how to easily integrate SQL Server data in the Premium Data Flow Components documentation section.

  5. MongoDB

    MongoDB is a cross-platform, multi-model, non-relational document-oriented database management system, available for free as an open-source community edition or paid licenses that include additional features and services. It is one of the most popular NoSQL document stores. MongoDB is offered as a managed multi-cloud service with distribution across AWS, Azure, and Google Cloud, or for implementation on a self-managed on-premises infrastructure. As a primary document-oriented database system, it uses flexible JSON-like documents with optional schemas instead of tables and rows to process and store data. MongoDB also supports key-value, spatial, graph, search engine, object, and time series data models.

    MongoDB can be easily integrated with any application or data source by using KingswaySoft's MongoDB Connection Manager, Source, and Destination components, found in SSIS Productivity Pack. These components empower developers with many configurable options and advanced settings to successfully achieve performant bi-directional data integration. Read more on how to streamline your MongoDB integration in the NoSQL documentation section.

  6. Redis

    Redis (Remote Dictionary Server) is an open-source, in-memory data structure store used as a message broker, cache, and multi-model distributed database, with support for key-value, document, graph, spatial, search engine, and time series database models. Initially known as Redis Labs, after original author Salvatore Sanfilippo left the project, it was shortened to Redis. Multiple world-known companies use Redis, such as Twitter, Snapchat, GitHub, and Stack Overflow.

    Redis supports multiple abstract data structures, including hashes, lists, geospatial indexes, strings, sorted sets, bitfields, bitmaps, HyperLogLogs, and streams. Furthermore, because Redis data is stored in memory, it delivers high performance with low latency, making it possible to handle millions of requests per second, with response times in sub-milliseconds. This capacity for processing a magnitude of real-time data has made Redis a popular choice for social media applications, real-time analytics, financial services, internet of things, and more.

    Solve Redis integration challenges and sync its data with any application or data source via Redis Connection Manager, Source, and Destination components, found in KingswaySoft's SSIS Productivity Pack. These components allow developers to efficiently achieve bi-directional data integration. Read more on how to facilitate Redis data integration in the NoSQL documentation section.

  7. Elasticsearch

    Elasticsearch is an open-source search and analytics engine based on the Apache Lucene library. It was released in 2010, and since then it has evolved into one of the most popular search engines. Well-known corporations across different industries, such as Netflix, Uber, Slack, Microsoft, Adobe, and Audi, use Elasticsearch. It supports all data types, including geospatial, numerical, textual, structured, semi-structured and unstructured. One of its key features is the Elasticsearch API, which makes easy to search and find data.

    Elasticsearch can be integrated effortlessly with any other application or data source using KingswaySoft's Elasticsearch Connection Manager, Source, and Destination components found in the SSIS Productivity Pack. Read more on how to easily integrate Elasticsearch in the REST Components documentation section.

  8. MariaDB

    MariaDB is a free and open-source community-developed fork of the MySQL RDBMS. It is primarily a relational DBMS, with multi-model support for other database systems, such as Document stores, Graph, and Spatial DBMS. MariaDB also offers a cloud database called SkySQL (MariaDB SkySQL Cloud Database), which supports real-time analytics. It was developed by MySQL's original developers and creator Michael Widenius, after MySQL got acquired by Oracle Corporation. In the same way that MySQL was named after Michael's older daughter, My, MariaDB was named after his other daughter, Maria. MariaDB is intended to remain free and maintains high compatibility with MySQL, making it often possible to work as a drop-in substitute for MySQL. Prominent companies using MariaDB are Mozilla, Google, and ServiceNow.

    MariaDB integration with any other application, databse software system, or data source can be painlessly easy by using KingswaySoft's SSIS Productivity Pack. Read more on how to easily streamline your MariaDB data integration in our help manual documentation section.

  9. Oracle Database

    Oracle Database is a multi-model DBMS developed and marketed by Oracle Corporation. This 2024, Oracle advanced one place to number 9, moving DynamoDB to number 10. Oracle's database system started as a relational database model but now provides much more, having the ability to store and process data using multiple approaches, such as in-memory, NoSQL, and SQL, all in one cloud database solution. In other words, it is an all-inclusive database system offering multiple solutions, including data marts, operational reporting, data lakes and warehouses, and batch and online transaction processing. Furthermore, it utilizes machine learning to automate routine tasks, guaranteeing increased performance, efficiency, security, and reliability. Oracle Database is offered with different services and products to meet the needs and budgets of its customers, such as Oracle NoSQL Database and Oracle MySQL HeatWave.

    Oracle Database integration with any other application, database software system or data source can be painlessly easy using the Premium ADO.NET components found in KingswaySoft's SSIS Productivity Pack. Read more on how to easily integrate Oracle Database in the Premium Data Flow Components documentation section.

  10. Amazon DynamoDB

    Amazon DynamoDB is a fully managed, serverless, proprietary NoSQL DBMS designed and sold by Amazon under the Amazon Web Services (AWS) product portfolio. DynamoDB can be considered a multi-model database with support for document data structures and key-value stores. This database software system makes use of hashing and B-trees for data management, and offers constant backups, built-in security, data import and export tools, and in-memory caching. It supports high-traffic and can be used to design patterns for deploying inventory tracking and shopping carts, handling millions of queries every second. Prominent companies that use DynamoDB are Zoom, Snapchat, and Disney.

    Amazon Dynamo DB can be easily integrated with any application or data source via the DynamoDB Connection Manager, Source, and Destination components, found in KingswaySoft's SSIS Productivity Pack. These components empower developers with many configurable options and advanced settings to successfully achieve performant bi-directional data integration. Read more on how to streamline your DynamoDB integration in the NoSQL documentation section.

Integrate the Top 10 DBMS with KingswaySoft's SSIS Productivity Pack

With the SSIS Productivity Pack, you can experience seamless integration between multiple DBMS, applications, and other data sources, without writing a single line of custom code. Packing more than 300 premium SSIS tasks and components, these powerful ETL tools will remove the complexity of database connections and bidirectional integration, enabling you to easily sync your applications with the most popular DBMS available today.

Thousands of enterprise clients from over 100 countries rely on our no-code SSIS Integration solutions to integrate data with various application systems to drive business efficiency and leverage information assets.

To read more about our DBMS connectivity solutions click here.

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About KingswaySoft

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