Published Mar 22, 2021

14 Best Database Management Software to use in 2023

By Joe Johnston

A good database is crucial to any company. An organization’s database stores all the pertinent details about the company, such as employee details, client records, transactional information, etc. Therefore selecting the correct database is critical. The database selection process can be complex, especially if you’re inexperienced. Fortunately, we’re made the process easier for you. We’ve compiled a list of the 14 best database management software to use in 2021. You can find the list below, and we’ve also covered important topics to help with comprehension of the subject.

What is a database?

As we live a large part of our lives on computers and the internet, we create vast amounts of data. For example, the words on this page are data. But for these words to exist, they must be stored somewhere - and that somewhere is a database.

A database stores and organizes data so information is easily accessed, managed, and updated.

What is database management software, and what are they used for?

Database management software, also known as DBMS software, is the interface between you, the user, and the data. As a user, you use a DBMS to store, manage, and update data and control access in a database environment. Database management systems vary, and there are several different types which we will cover later, but most of them include; a data library, auditing, data abstraction, security, and recovery support.

Types of database management systems

Database management systems come in several different types, each with its strengths and weaknesses. You don’t need to try all these types. You need to figure out which one works best for your business. To help you, I’ve added an explanation for each type below:

Relational - Relational database management systems (RDBMS) organize and store data in tables. These tables are linked together - which is where the term relational derives from (relationships between data/tables). Tables consist of fields (think table columns) and records (think table rows). SQL is the standard language for this type of database.
Document - Document store or document-orientated database systems are schema-less, which means they do not have a uniform structure, such as a table. This is why people refer to these types of databases as non-relational or NoSQL. Within NoSQL databases, columns can contain arrays (multiple values), and records can be nested.
Key-value - Key-value stores are simple in nature and consist of keys and values. Every single item within a key-value store is given a key and value. Due to its simplicity, this type of database is not great for complex data structures. However, they are well suited to use cases such as embedded systems.
Search engine - Search engines are NoSQL databases dedicated to search. As the amount of data we collect increases, so does the need for performant search capabilities. Apache Lucene is a critical player in a number of the best search engines available.
Wide-column - Wide-column stores utilize a similar structure to a relational database: tables, columns, and rows. But there is a critical difference: wide-column stores structure their data around columns rather than rows.
Graph - Graph databases use graph structures to store and sort information. These structures consist of nodes and relationships. Within this type of database, relationships are treated equally important as the data itself. If your application heavily revolves around relationships, such as social networks, this may be a good choice.
Time Series - As you can probably guess, this type of database is optimized for time series data (time-stamped records). Examples of applications that might use a time-series database are a wall street trading application, a smart home monitor, and a Covid Infection Rate application.

I have not covered additional database types, such as Multivalue database management systems and Object-Oriented database management systems. In both the cases above, relational databases have been extended to cover some of the features offered.

If after reading the above you are still not sure what database management system to choose, read the following three tips:

How much data are you storing? Different databases perform differently with varying amounts of data. Some databases will not serve you well if you have petabytes of data, for example. Also, when considering this, think of the future and how the databases scale.
A data modeling exercise will guide your decision. There are several different approaches to data modeling, but primarily you should consider the entities in your data model and what values are stored for each entity. I would advise you to draw an ERD (entity-relationship diagram).
You can use more than one database management system, for example, a Document Store with a Search Engine.

Check out our guide to system integration vs software development .

14 best database management software examples

Below, I have listed my 14 best DBMS examples. Some examples support multiple types of models, but I have grouped them according to what I feel is their primary model type. For those of you who are considering building a web app / internal tool, I have also outlined whether the listed database is supported by Budibase - an open source development platform for building internal tools in minutes. If it is supported by Budibase, you can simply connect that database and build anything from dashboards, admin panels to approval applications in minutes.

Relational

1. PostgreSQL

In many situations, PostgreSQL is the go-to solution for performing complicated, high-volume data operations. It is feature-rich and object-relational, ACID-compliant, and highly concurrent.

USP - Supposts a big subset of the SQL standard
Pro: Feature-rich. Out of all the relational databases, PostgreSQL comes with the most features.
Con: Read-only operations can feel slow
When would I use this: When performing data operations.
Secondary models: Document store
License: open source
Supported by Budibase : Yes

2. Oracle

Oracle DBMS a widely used relational DBMS, developed and maintained by Oracle since the 80s. It is a database commonly used for running online transaction processing, data warehousing, and mixed database workloads.

USP - Enterprise proven
Pro - Efficient administration and security
Con - Oracle DB is not very elegant to work with, and it can feel sluggish at times. It’s also not open source and can get quite expensive.
When would I use this - when building enterprise applications.
Secondary models - Document store, Graph DBMS
License - Commerical
Supported by Budibase - No

3. MySQL

MySQL is another database from Oracle, but this one is free and open-source. Historically, I always associated MySQL for its speed and simplicity. In recent versions, the creators changed the engine, adding additional functionality and the detriment of speed. These additional features are essential for enterprise clients and include transactions and key constraints. MySQL was my go-to relational DB, but I’ve since moved to PostgreSQL due to its handling of concurrency.

USP - It’s simple to use, and easy to get started
Pro - Reliability, and simplicity - it’s the world’s most popular DBMS, with 39% of developers using it in 2019.
Con - It used to be faster and lacks the functionality of other similar DBMSs.
When would I use this - When building simple web applications.
Secondary models - Document store
License - open source
Supported by Budibase: Yes

4. Snowflake

Snowflake is a cloud solution for data warehousing, data lakes, data engineering, data science, data application development, and securely sharing and consuming shared data. Its growth in recent years has been inspiring, and for a good reason. Snowflake can automatically scale up and down to get the right balance of cost vs. performance. Its primary

USP - its ability to separate compute from storage which allows for better costing.
Pro - Scalability and its separation of compute and storage.
Con - It heavily depends on major cloud platforms (AWS, GCP, Azure). If they go down, it can be problematic. But, we’re scraping the barrel here.
When would I use this - For more people, a database will house your data sufficiently. For large organizations with growing data storage needs, a data warehouse is more scalable.
Secondary models - None
License - Commerical
Supported by Budibase - No

5. Clickhouse

ClickHouse is a column-oriented database management system (DBMS) for the online analytical processing of queries (OLAP).

USP - Speed! Column-oriented databases are better suited to OLAP scenarios: they are at least 100 times faster processing most queries.
Pro - Speed at processing queries. Low requirements for data consistency.
Con - It’s pretty limited in scope, focusing on data analytics and nothing else.
When would I use this - OLAP/analytics
Secondary models - None
License - Open Source
Supported by Budibase - No

Document Store

6. MongoDB

On the MongoDB website, they describe themselves as a general-purpose, document-based, distributed database built for modern application developers and the cloud era. We feel this description is pretty solid and summarizes the critical ingredients of this Budibase favorite.

USP - MongoDB’s horizontal, scale-out architecture can support vast volumes of both data and traffic
Pro - It’s community, and documentation is the best when comparing all document store databases.
Con - Due to the lack of atomic transactions, the speed is comparatively low compared to NoSQL.
When would I use this - When I need to represent data with natural clusters and variability over time or in its structure.
Secondary models - Spatial DBMS and search engine.
License - Open Source
Supported by Budibase - Yes

7. Amazon DynamoDB

On its website, Amazon describes DynamoDB as a key-value and document database that delivers single-digit millisecond performance at any scale. It’s a fully managed, multi-region, multi-active, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and support peaks of more than 20 million requests per second. Budibase uses DynamoDB to make the data operations within its hosting portal.

USP - DynamoDB is a fully managed service reducing the number of operations required to run the solution.
Pro - DynamoDB comes with out-of-the-box security, and the IAM solution is reliable.
Con - Only available on AWS. It can also get costly quickly.
When would I use this - When using building low throughput apps.
Secondary models - Key-value store
License - Commerical
Supported by Budibase - Yes

8. CouchDB

CouchDB is a document store database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. Access your documents and query your indexes with your web browser via HTTP. With CouchDB, you can Index, combine, and transform your data with JavaScript.

Budibase uses CouchDB for its database, and we’re particularly huge fans of the replication functionality.

USP - The Couch Replication Protocol lets data flow seamlessly between server clusters to mobile phones and web browsers, enabling a compelling offline-first user-experience while maintaining high performance and strong reliability.
Pro - You get management/access control for free. And, of course, replication.
Con - Poor documentation and querying can be slow for large data sets.
When would I use this - When you need offline support.
Secondary models - Spatial DBMS
License - Open Source
Supported by Budibase - Yes

Key-value

9. Redis

Redis is an open-source in-memory data structure store used as a database, cache, and message broker. For me, Redis is the best solution for storing cache.

USP - Redis is written in C and is blazingly fast. Faster than any other caching solution.
Pro - Supported by most languages, including JavaScript, Go, Java, and more.
Con - Within Redis, data is sharded based on the hash-slots assigned to each master. If the master is down, you will lose that data.
When would I use this - When you need to store cache.
Secondary models - Spatial DBMS, document store, search engine.
License - Open Source
Supported by Budibase - No.

Search Engine

10. Elasticsearch

Elasticsearch is a distributed document-oriented search engine that stores data in the form of a document. In other words, it is a quick and easy way to implement search in your application.

USP - It’s pretty straightforward to scale
Pro - Elasticsearch is more dynamic than other options, as data can move around the cluster and nodes come and go.
Con - It only supports JSON.
When would I use this - when I need to search for JSON-related data.
Secondary models - Spatial DBMS, document store, search engine.
License - Open Source
Supported by Budibase - Yes.

Wide-column

11. Cassandra

Cassandra is a wide-column database. It offers continuous availability, high scalability and performance, robust security, and operational simplicity while lowering ownership’s overall cost.

USP - No single point of failure ensures 100% availability
Pro - Write speed is breakneck due to its architecture
Con - Aggregation functions are not efficient
When would I use this - I would not use Cassandra when ACID support is required, but if you have a scenario where the data model is unpredictable, I would consider Cassandra.
Secondary models - None
License - Open Source
Supported by Budibase - No.

Graph

12. ArangoDB

ArangoDB is a free and open-source native multi-model database system developed by ArangoDB GmbH. The database system supports three data models with one database core and a unified query language AQL. The query language is declarative and allows the combination of different data access patterns in a single query. Neo4j was the graph DB of choice for so long, but ArangoDB is now my go-to choice for the reasons below.

USP - Data relationships are natively stored as first-class citizens as a graph edge
Pro - Performant with highly connected datasets
Con - Switching graph stores can be complex due to poor query standards
When would I use this - When relationships are a critical component of my data architecture - social networks, for example.
Secondary models - document store, key-value store, search engine
License - Open Source
Supported by Budibase - Yes

13. Neo4j

Neo4j is a native graph database built from the ground up to leverage data and data relationships. It is the largest graph database ecosystem with more than 15 million downloads, and Docker pulls. It is also one of the oldest and is more well-known than Arangodb.

USP - Robust graph visualization tools
Pro - Graph edges can store labels
Con - You can only have one Graph per Neo4j instance
When would I use this - Until I experienced Arangodb, I would have chosen Neo4j without thinking. Now, I would select Arangodb due to its feature-rich platform. I suppose I would choose Neo4j if I heavily relied on Spring.
Secondary models - Spatial DBMS
License - Open Source
Supported by Budibase - No

Time-series

14. InfluxDB

InfluxDB is an open-source time-series database from the InfluxData company. It is widely used to monitor applications, infrastructure, IoT, and data analysis.

USP - Most performant solution in its class and supports multiple data-types.
Pro - InfluxDB supports a vast number of client libraries and languages.
Con - Due to its schema-less design, some database functions are not supported - joins!
When would I use this - InfluxDB makes it a fantastic choice for DevOps monitors, real-time analytics, and IoT and Sensor Data.
Secondary models - Spatial DBMS
License - Open Source
Supported by Budibase - No

Conclusion

As I previously highlighted, your database management system choice will come down to size, scaling, and architecture.

I hope you enjoyed this post and it’s helped you on your journey with selecting a database. As we explore more database management systems, we will continue to add to this list. If you currently research databases with the ambition of building a web app/internal tool, you should consider Budibase . Budibase is an open-source development platform for building internal tools in minutes and on your own infrastructure. Budibase has its own internal database and supports data from several databases mentioned in the list above (PostgreSQL, Mongo, Couch, MySQL, Elasticsearch, and more).

Once again, thanks for reading and best of luck on your journey.