Best Database To Choose For Your Application In 2023

Every website or app handling data needs a database to store, recover, arrange, and alter said data. It is an essential part of back-end development as it ensures that all the data on the app, including the code itself and any user information, are safely stored in one place and can be accessed as quickly and productively as possible. Different databases have different priorities and different usability. The choice of a database can have a profound impact on what kind of operations your application can perform and what features it can offer during its development and runtime.

There are many different approaches to analyzing the different database types. The primary division is made on the mode model. And it is into SQL and NoSQL types. A SQL database also called a relational database system (RDBMS), is table-based, where each data is relationally linked to another. Such databases work on queries and produce results based on them. It is a go-to option for apps that need structure or multi-row transactions. One of the SQL fundamentals is ACID compliance (Atomicity, Consistency, Isolation, Durability). The ACID-compliance is a preferred option if you build, for instance, eCommerce or financial applications where database integrity is critical. The NoSQL database, unlike SQL, does not structure the data. NoSQL databases work on JSON (JavaScript Object Notation) and XML. For big data applications and when flexibility plus scalability are the central priority, NoSQL databases will be the right choice.

Based on the payment type, databases can be grouped into open-source and commercial. An open-source database is a database with open-source code that anyone can view. It is usually free to download and offers extensive community support, but technical support is limited. Commercial databases are created for commercial purposes. It means the code is not accessible to unauthorized users, only programmers or organizations who have created the code can access and change it. Commercial databases have guaranteed technical support. So, if you need more service and technical support, the latter will suit your needs better. SQL and NoSQL databases can be both open-source and commercial.

As to the type of hosting, databases can be on-premises or Cloud. An on-premises database resides in-house. All the software, infrastructure, and administration required for its management and maintenance are local. With large-scale enterprises, the storage moves to a local data center. Cloud databases may be traditional self-managed or fully managed databases as a service (DBaaS). The self-managed database is installed and hosted on a virtual machine and maintained by an in-house IT team. In the case of a DBaaS, it is the cloud provider who is responsible for maintenance, administration, security, upgrading, etc. Cloud databases provide such benefits as speed, scalability, and reduced costs. All the data stored in the cloud database has to be encrypted.

And finally, a database can be centralized or distributed. A centralized database is stored and managed in a single location. It scales mainly vertically as one ultimate machine does the work. Its main advantage is that it has minimal data redundancy and better data integrity. Distributed databases store information across different physical sites offering zero downtime. They are usually horizontally scalable, as multiple smaller machines do the work. The database may reside on multiple CPUs on a single site or spread out across various locations.  

According to the Tech Stack Overflow survey 2022, today's top three open-source SQL databases include MySQL, PostgreSQL, and SQLite. The principal commercial SQL databases are Oracle and Microsoft SQL Server. The leading players among NoSQL databases are MongoDB, Redis, Elasticsearch, and Firebase. So let's determine the ultimate database in each group and use cases of each of them. And our analysis starts with open-source SQL databases.

MySQL has been one of the market's most popular open-source RDBMS since its invention in 1995. It is written in C and C++ and, as the name says, uses a structured query language (SQL). Now it is owned by Oracle. According to the PYPL Index and DB-Engines Ranking, it is the second most popular database after Oracle. Cloud providers such as Amazon AWS, Google Cloud, Microsoft Azure, Oracle, DigitalOcean, and Heroku offer a wide variety of MySQL databases that can be purchased, configured, and scaled as needed.

MySQL features are:

• MySQL is a free, open-source RDBMS. Oracle also offers a MySQL Enterprise version, including the most comprehensive set of advanced features, management tools, and technical support.

• MySQL is platform-independent so that it can run on all popular operating systems, such as Windows, Linux, Solaris, OSX, and FreeBSD. 

• MySQL supports the major programming languages, including C, C#, C++, Java, JavaScript (Node.JS), PHP, Ruby, and Python.

• MySQL is ACID compliant through the InnoDB and NDB Cluster Storage mechanisms.

• MySQL is a centralized database by design. But it can be used as a distributed database using MySQL Cluster CGE. With its MySQL Cluster, it offers multi-master ACID transactions. Additionally, MySQL supports several types of replication, which help set up database backups or scale the database horizontally. 

• MySQL supports one-way, asynchronous replication, in which one server acts as the source while one or more other servers act as replicas.

• MySQL is very user-friendly. Its syntax and format are fixed, declarative, and easy to use. With exhaustive documentation and a large community of developers, it is easy to get started with MySQL.

• MySQL supports the following data types: numeric types, date and time, character, spatial, and JSON types.

• MySQL offers various utilities with memory caches to make working with MySQL servers easier.

PostgreSQL is an open-source object-relational database management system (ORDBMS) developed in 1996. It is written in C and also uses a structured query language (SQL). PYPL Index and DB-Engines Ranking put it as the fourth most popular database. It is preferred by businesses that deal with huge amounts of data. There are also various cloud versions of the PostgreSQL database from the primary providers: Amazon, Google Cloud, Microsoft Azure, Elephant,Heroku, CitusDB, etc.

PostgreSQL features are:

• PostgreSQL is a free database. There is no fee, even for use in commercial software products.

• PostgreSQL is platform-independent and supports many operating systems, such as Windows, Linux, Unix, FreeBSD, HP-UX, NetBSD, OpenBSD, OS X, Solaris, and Unix.

• The supported programming languages for PostgreSQL include C, C++, Java, JavaScript (Node.js), PHP, Python, and others.

• PostgreSQL is fully ACID compliant, i.e., queries maintain data integrity and return the same output without error. 

• PostgreSQL is not natively distributed. For a distributed version of PostgreSQL 3rd, party extensions  Citus Data and Postgres-XL can be used.

• Postgres offers a wide variety of data types such as Numeric, Date/Time, Character, Boolean, Enum, Geometric, Network Address, JSON, XML, Hstore, Arrays, Ranges, and Multiparts.

• PostgreSQL supports streaming replication. It allows the updated information on the primary server to be transferred to the standby server in real time so that the databases of the primary server and standby server can be kept in sync.

• PostgreSQL maintains data consistency by using a multiversion concurrency control, which makes it stand out from traditional database systems, which use locks for concurrency control.

• PostgreSQL offers features such as Inheritance and Function Loading. 

• PostgreSQL has a low learning curve but is more complicated than MySQL. The database is well-supported by its active community. 

SQLite is an open-source embeddable, in-process RDBMS that runs on the client's machine in local storage. The database was created in 2000. It is written in the C programming language. The lite means lightweight, not in terms of its capabilities, but in terms of setup complexity, database administration, and resource usage. The database requires no configuration (setup or administration) and no server. Since SQLite is serverless, there is no need to run the server in the Cloud. SQLite works like a library included in the program and allows reading and writing a SQLite file using SQL-like queries.

The main SQLite features are:

• SQLite is a free database. It offers several extensions for compression and encryption for a one-time fee each. It also provides several commercial support packages for an annual fee.

• Unlike other RDBMS, such as MySQL or PostgreSQL, which require a separate server process to operate, SQLite does not require a different server process or system to operate and is thus serverless. SQLite reads and writes directly to ordinary disk files. 

• The SQLite file format is cross-platform. Android, *BSD, iOS, Linux, Mac, Solaris, VxWorks, and Windows (Win32, WinCE, WinRT) are supported out of the box. It is easy to port to other systems.

• Most programming languages have built-in support for SQLite, including C, C#, C++, Go, Java, JavaScript, Objective-C, PHP, Ruby, Tlc, and Python.

• All transactions in SQLite are fully ACID-compliant. 

Thus, SQLite is a top lightweight database that works great for low to medium-traffic websites. Because of its lightweight, it is perfect for embedded applications on mobile devices. In other cases, the choice for an open-source relational database management system is mainly between MySQL and PostgreSQL. PostgreSQL vs. MySQL is a crucial decision for choosing an open-source relational database management system. When comparing MySQL and PostgreSQL, the former is more user-friendly, and building a project from scratch takes less time, but the latter is considered a more advanced database. PostgreSQL supports a broader range of data formats. Replication in MySQL is one-way asynchronous, while PostgreSQL supports synchronous replication. Postgres performs better because it supports concurrent writes without the need for read/write locks. It also implements transaction isolation and snapshots and is entirely ACID compliant. MySQL performs better only for read-intensive processes. Still, both DBMSs are reputable solutions that can compete with such enterprise solutions as Oracle or Microsoft SQL Server.

Let's continue our analysis with the top commercial databases, Oracle and Microsoft SQL Server. Before we start, it is worth mentioning that the Tech Stack Overflow survey 2022, PYPL Index, and DB-Engines Ranking also list Microsoft Access in the top 10 list of most popular databases. MS Access is a database management system that comes with the Microsoft 365 suite. Microsoft produced it in 1992 during the PC revolution as a solution to be used instead of Excel when it became too complicated and cumbersome. It was a good choice before the focus shifted to web and mobile apps, and more complex and programming-heavy MySQL solutions were developed. The future of software applications focuses on cloud-based, web, or mobile-based apps, while MS Access is the last PC-only database. It works neither with the web nor with mobile. It also doesn't scale well or work outside of its own ecosystem. In other words, it's not a standard like any other databases like MySQL, PostgreSQL, or even SQLite. It still occupies the top ten positions in different rankings, most likely because there are business/industrial applications where a windows environment is needed, and a browser or app-based solution will not work. And some companies still use it for some legacy reason. However, the market now opts for more advanced low-code databases or more heavyweight user-friendly cloud solutions. So, if you need a commercial relational database, the choice is between Oracle and MS SQL Server.

Oracle is the world's first commercially supported RDBMS, mainly designed for enterprise grid computing and data warehousing. Enterprise grid computing creates large pools of modular storage and servers, where the storage mechanism is achieved by creating logical and physical structures. Oracle has been the most widely used system since its creation in 1979. PYPL Index and DB-Engines Ranking put it as the number one popular database. It supports SQL to interact with the database and is built in assembly languages such as C, C++, and Java. For cloud deployments, Oracle offers its managed cloud platform (PaaS), Oracle Database Cloud Service, in which the databases are hosted on Oracle infrastructure. Alternatively, it is possible to choose a different cloud provider and set up an Oracle database on Azure or Oracle database for AWS. 

The Main Oracle features are: 

• Oracle is a proprietary RDBMS. It has an Enterprise edition suitable for large businesses that need a high-powered solution. Its Standard Edition 2 is ideal for small and medium enterprises. While, its Personal edition is eligible for a Windows-only, one-user program. 

• Oracle offers an ACID transactional guarantee. 

• Oracle Database can run on various platforms such as AIX, HP-UX, Linux OS X, Solaris, Windows, and z/OS. 

• Oracle Database developers have a choice of languages for developing applications—C, C#, C++, Java, Javascript, Objective-C, PHP, PL/SQL, and Visual Basic.

• Oracle's is PL/SQL allowing users to group procedures into packages.

• Each new connection to the database is treated as a new transaction with Oracle. Until the transaction is committed, it can be rolled back, and all the changes in the statement can be undone. It provides flexibility and allows for greater manual control. 

• Oracle runs very quickly as it allows reading during the writer process, i.e., readers and writers do not block one another. Therefore, while queries still see consistent data, both read committed and serializable isolation provides a high level of concurrency for high performance.

• Oracle syntax is quite complex compared to the traditional SQL syntax used by popular RDBMSs and NoSQL databases.

Microsoft SQL Server is a centralized RDBMS developed by Microsoft in 1989. It is a software product known as a database server. SQL Server is mainly written in C++. PYPL Index and DB-Engines Ranking gave it a bronze-winning place among the most popular databases. The most popular vendors for providing the cloud version of the database are, as usual, Google  AWS and Azure.

The Main Microsoft SQL features are: 

• Microsoft SQL is a proprietary RDBMS. The database has an Enterprise edition for large and data-driven companies. It also has a Standard edition for organizations that don't need that much computing power.

• MS SQL Server runs on Windows and Linux only.

• Supports Server-side scripting via T-SQL, C#, C+, Java, Javascript, PHP, R, Python, Visual Basic, and Ruby.

• MS SQL has excellent Microsoft support with tools such as SQL Server Profiler, SQL Server Management Studio, BI tools, and Database Tuning Advisor.

• MS SQL will, by default, execute and commit each task or command sequentially and individually. It makes it hard or even impossible to roll back a transaction if an error occurs in the middle of the process.

• Microsoft SQL provides built-in features such as Data classification, protection, data monitoring, alerts on malicious activities, security breaches, misconfiguration, and many more.

Thus, the Oracle Database is more complex to manage than MS SQL Server. It has a higher learning curve and is more expensive to license. For startups and modern companies, Oracle is too burdensome to manage. Oracle charges additional for their tools, while Microsoft tools are free with the SQL Server license. But with this, Oracle also has an advantage over Microsoft in terms of core database features and functionality. In other words, both databases are for large organizations, but Oracle is for larger organizations where a larger database is needed.   

And now, let's proceed to the analysis of leading NoSQL databases: MongoDB, Redis, Elasticsearch, and Firebase. Among them, MongoDB, Redis, and Elasticsearch are open-source. At the same time, Firebase stands slightly separately in the list as it is a purely cloud-hosted and commercial document-oriented database system. 

MongoDB, released in 2009, is the first database developed to handle Document Data. According to all rankings, Tech Stack Overflow survey 2022, PYPL Index, and DB-Engines, it is the leading NoSQL Database. It is written in C++, JavaScript, and Python languages. The database is highly scalable, flexible, and adaptable. It is possible to use MongoDB for applications that contain both structured and unstructured data. It is available both for deployment on self-managed infrastructure and as a fully managed cloud service. MongoDB cloud Database-as-a-Service Atlas can be deployed on any of the major cloud providers, like AWS, Microsoft Azure, and Google Cloud.

The Main MongoDB features are: 

• MongoDB is a general-purpose, free, and open-source database. It also has such licenses as free Community Server, commercial Enterprise Server, and SaaS Atlas (managed in Cloud).

• MongoDB runs on Linux, OS X, Solaris, and Windows.

• MongoDB currently provides official driver support for all popular programming languages like C, C++, C#, Java, Node.js, Perl, PHP, Python, Ruby, and Go.

• MongoDB Inc. also offers a full-text search engine (Atlas Search) and data lake, a fully managed storage solution optimized for analytical queries (Atlas Data Lake).

• MongoDB is a distributed database where developers can create clusters with real-time replication and fragment large collections across multiple structures.

• MongoDB is ACID-compliant from 4.0 version and onward. It offers distributed multi-document ACID transactions with snapshot isolation. With snapshot isolation and all-or-nothing execution, applications maintain transactional data integrity, even across highly distributed sharded clusters.

• MongoDB has a powerful MongoDB Query Language (MQL) similar to SQL queries in SQL Database language with complex querying using an aggregation pipeline. 

Redis, developed in 2009, is an open-source distributed in-memory key-value data platform used as a cache, message broker, database, and streaming engine. In-memory means the data is not written to disk but is kept in volatile RAM. This in-memory feature allows high-speed access to data, which is why Redis is often used as a cache and a secondary database to support the primary database. It means that the application first requests information from Redis rather than from the primary node. If the data were previously stored in the Redis cluster, it would pop up as a response in a blink of an eye without any impact on the primary database node. Leveraging cache helps to optimize performance significantly. According to the Tech Stack Overflow survey 2022, it is ranked the second most loved database platform after PostgreSQL. Redis is implemented in C and can be deployed on-premises, across clouds, and hybrid environments. Vendors offering Redis cloud databases are AWS, Google Cloud, Azure, Scalegrid, Oracle, or Digital Ocean.

The Main Radis features are: 

• Redis is free and open-source. It has the Redis Enterprise edition, which is closed-source and requires a commercial license from Redis Ltd.

• Redis runs on BSD, Linux, OS X, and Windows.

• Supported languages include Java, JavaScript (Node.js), Python, PHP, C, C++, C#, C-Objective, Swift, Dart, Ruby, Go, and many others. 

• Redis stores data using data structures and primary supports: strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyper-logs, geospatial indexes, and streams.

• Redis transactions are not fully ACID compliant. It does not guarantee consistency because Redis is at risk of losing writes. It also does not ensure durability. The database's durability can be increased by Redis append-only file feature (AOF). When this feature is enabled, the node writes all commands that change cache data to an append-only file. However, such an approach may affect performance.

• Redis employs a primary-replica architecture and supports asynchronous replication where data can be replicated to multiple replica servers. 

• Redis has Advanced Cache functionality. It supports various eviction policies, including Least Recently Used (LRU), Least Frequently Used (LFU), Random Eviction, and Shorter Time-to-Live (TTL).

Elasticsearch, released in 2010, is an open-source full-text search and analytics engine with a distributed, multi-tenant capability and a REST API. The database is written in Java. It is a near real-time search platform that uses Apache Lucene indexes to store and retrieve its data for language-based searches. Java library Lucene is the industry standard for the full-text search purpose. The database can be deployed on-premises or with any cloud vendor like AWS, Google Cloud, or Microsoft Azure using a managed service or a self-managed approach.

The Main Elasticsearch features are: 

• Elasticsearch is a document-oriented distributed database. It is free of cost and open source. Additional free features are available under the Elastic License and paid subscription providing access to support as well as advanced features such as alerting and machine learning. 

• Elasticsearch runs on all operating systems with a Java Virtual Machine.

• Elasticsearch supports the following programming languages: .Net, Java, JavaScript, Perl, PHP, Python, and Ruby.

• Elasticsearch offers real-time search and analytics for structured, unstructured, numerical, or geospatial data.

• Elasticsearch does not support ACID transactions for changes involving multiple documents. It uses Lucene, built for speed, but not redundancy. So the database has high-speed performance, but at the same time, it is more susceptible to data loss. Quite often, Elasticsearch is used as a search engine or as a way to improve performance, while the main data store is a relational database, and ACID transactions are dealt with in the relational database.

• Elasticsearch is Part of the "Elastic Stack" (Elasticsearch, Kibana, Logstash, Beats). It is one of the most popular observability platforms organizations use to gain granular insights and context into the behavior of applications running in their environments.

Firebase is a purely cloud-hosted and commercial document-oriented database system. It stores and synchronizes data in real time. Firebase, released in 2012, is owned by Google, designed and scaled on Google resources, and is only available on the Google Cloud Platform. Being a Cloud-hosted solution, it allows access to data from any device, including iOS and Android. Firebase is part of a growing trend known as "Back end as a service". Initially, it started as a real-time database, and now it is a development platform that provides developers with various tools and services to help them develop quality apps. 

The Main Firebase features are: 

• Firebase is not open-source but a proprietary service. For now, it does not offer Enterprise contracts and support.

• Firebase is available only on the Google Cloud Platform. Being a cloud-hosted solution, it does not allow any modifications to the database.

• Firebase uses key-value, wide-column, graph, or document store and has dynamic schemas to facilitate unstructured data. Data is synchronized to every connected client in real time.  

• It is possible to use any programming language with Firebase, as all languages make API calls to Firebase accounts to retrieve JSON objects (data stored in a key-value pair format). 

• Firebase comes with mobile and web SDKs allowing it to build apps without servers. Google takes care of the server. Developers can also execute back-end code that responds to events triggered by the database using Cloud Functions for Firebase.

• Firebase uses a local cache on the device to serve and store changes in the offline mode. When the device comes online, the local data is automatically synchronized.

• Firestore is NoSQL designed for speed and scalability, but its query functionality is pretty limited.

Thus, we can conclude that the top NoSQL databases, MongoDB, Redis, Elasticsearch, and Firebase, are not actually competitors. Each can be considered a leader in its own domain. MongoDB has enhanced scalability, increased caching, analytics in real-time and great speed, providing dynamic performance. It is an excellent option for apps such as product catalogs or analytic platforms. Redis is great for caching, gaming, real-time analytics, chat/messaging, and media streaming apps. Elasticsearch is used massively as a search engine meant for working on large datasets in real-time, for instance, for eCommerce products and the observability of applications. It's also very helpful when creating or updating a customer's profile regarding the workload that real-time engagement usually demands. Developers often pair it with other SQL & NoSQL databases. A Firebase database can be a good option when your software deals with real-time data that needs to be synchronized between different browsers and devices, for instance, messaging apps, social media apps, and gaming apps.

Choosing the correct database can be challenging. It depends on how much and what type of data your app needs to manage, how many users are expected, where they are, and how complicated the front end is. On top of it, your app will evolve over time, so the needs can also change. Choosing the wrong database can result in costly migrations or the necessity to use multiple databases to handle the new needs of your app. It will add complexity to development cycles and increase costs. Scrumlaunch is here to help you select the right database for your software application based on your business model and needs.