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Most companies today need some kind of database, but it’s not always easy to know which one would best fit your needs. They started out as sets of punch cards, but are now monstrous databases capable of storing petabytes of information.

That can make it pretty tough on a new user looking for a database software solution for their business. But there are three database types we see most frequently: relational databases, document databases and graph databases.

Relational databases store and manage data in a traditional table format, with each piece of data organized into a row and a column. Columns hold the data of a single type or field, like first name, order number, or the image link of a product logo. Rows create the relationship between these data points.

For example, rows can associate a first name to a last name and then to a user name, email address, and customer ID.

Businesses use relational databases to maintain the data from their applications and ensure they always have access to critical customer information, product data, social data, and financial particulars like purchases, fulfillment, revenue, and expenses.

Almost all use a form of SQL as their query language, and most adhere to the ACID set of properties to ensure reliable transactions: atomicity, consistency, isolation, and durability.

Relational databases are generally chosen due to their simplicity in comparison to NoSQL databases, such as object-oriented databases, document databases, and graph databases. Those looking for a relational database solution with little budget also have options with free database software.

MySQL has been around for more than 30 years, and it’s evolved a lot since then. It’s still free and open-source, but there are a lot more GUI and command line tools for managing and accessing MySQL. Those can be found in our Non-Native Database Mgmt Systems software category.

Platform: Linux, Windows, and Mac.

Languages: C, Java, SQL, C++, Perl, Python, Tcl, and PHP.

Features:

The tool provides Scalability and Flexibility
The tool has web and data warehouse strengths
It provides high Performance
It has Robust Transactional Support

SQL Server 2017 brings the power of SQL Server to Windows, Linux and Docker containers for the first time ever, enabling developers to build intelligent applications using their preferred language and environment. Experience industry-leading performance, rest assured with innovative security features, transform your business with AI built-in, and deliver insights wherever your users are with mobile BI.

Microsoft SQL has been around since the late 1980s and powers other hugely popular companies like NASDAQ, Yahoo and Dell.

Platform: Docker Engine, Ubuntu, SUSE Linux Enterprise Server, and Red Hat Enterprise Linux.

Languages: C, C++, Java, and C#

Features:

It provides integration of structured and unstructured data with the power of SQL Server and Spark.
The tool offers scalability, performance, and availability for mission-critical, intelligent applications, data warehouses, and data lakes.
It offers advanced security features to protect your data.
Access to rich, interactive Power BI reports, to make a faster and better decision.

Though it is not quite as old or widely used, it has still been around for more than 20 years and powers giant corporations like ADP, Fujitsu and Cisco. According to its site, 30 percent of tech companies use PostgreSQL as the core for applications as of 2012.

The tool has a liberal open-source license, which allows users to freely modify code for their specific company’s needs. Some of its core features include table inheritance, nested transactions and asynchronous replication.

Platform: Mac, Windows, and Linux.

Languages: PL/Tcl, PL/pgSQL, PL/Python, and PL/Perl.

Features:

Compatible with various platforms using all major languages and middleware
Standby server and high availability
The tool has mature server-side programming Functionality
Log-based and trigger-based replication SSL.
It offers a most sophisticated locking mechanism.
Support for multi-version concurrency control
It provides support for client-server network architecture
The tool is Object-oriented and ANSI-SQL2008 compatible
PostgreSQL allows linking with other data stores like NoSQL, which act as a federated hub for polyglot databases.

Document databases store related data in document format. These databases support document creation, retrieval via query, updating and editing, and deletion of information within the documents.

Document stores, because of their lack of structure, are easily scalable by utilizing clusters.

Document-oriented databases allow for a variety of document model types, but house relevant data together in a semi-structured schema. The semi-structured schema allows metadata to be stored within the documents.

Document databases store information in a range of encoding, or languages, including YAML, JSON, BSON, and XML, the latter of which can be qualified as its own class of databases.

MongoDB is the leading modern, general purpose database platform, designed to unleash the power of software and data for developers and the applications they build. Headquartered in New York, with offices across North America, Europe, and Asia-Pacific, we are close to where you do business.

The free and open-source tool functions across platforms and provides drivers for 10-plus languages, including Python, Java and C++. Its core features are indexing, ad hoc querying and high-availability data replication.

Platform: Cross-platform

Languages: C#, C, Java, C++, Perl, Scala, Ruby, etc.

Features:

Fully Automated scale provision, and manage complex, highly available, multi-node clusters with easily with API calls.
This tool allows you to create globally distributed clusters.
Easy to restore data when needed.
It offers visualization, monitor, and alert on more than 80 metrics which track your cluster's health or integrate with third-party monitoring solutions.
The tool has a powerful query language
It uses rich JSON documents to store tables in a relational database.
It provides MongoDB Atlas, which is a global cloud database.

CouchDB is a few years older than MongoDB, but uses the same file notation format, JSON. It was developed by open-source giant Apache and released in 2005. Some large companies using CouchDB are the BBC, Sophos and Canonical.

It’s completely open source, like almost all Apache tools. Some of its core features are ACID Semantics, offline editing and a distributed architecture perfect for data replication.

Platform: Cross-Platform

Languages: Java, Python, C++, Perl, C, JavaScript, PHP, etc..

Features:

It enables you to run a logical database server on any virtual machines.
CouchDB tool works with external tools like load balancers, HTTP, and proxy servers.
The too provides support of authentication and session.
CouchDB cluster enables you to save data redundantly.

DynamoDB is a fully managed offering from Amazon Web Services (AWS) as part of its suite of cloud products. It’s not totally free, and while AWS does offer a free tier with limited capabilities, be warned: If you exceed free-tier usage, you must pay the difference.

The free offering allows applications to handle up to 200 million requests per month, 2.5 million read requests per month from DynamoDB Streams and store 25 GB of data. Most of the paid offerings are scalable depending on application usage.

Platform: Cross-platform

Languages: Go, Node.js, Java, .NET, C#, Ruby, Python, PHP, and Perl.

Features:

Key-value and document data model support.
DynamoDB offers secondary indexes which provide the flexibility to query on any attribute.
Amazon DynamoDB Accelerator delivers fast read performance for your DynamoDB.
DynamoDB integrates with AWS Lambda to provide triggers.

Graph Database software solutions are another NoSQL type database that use graph structures for semantic queries. The tools are based on graph theory, where nodes represent data points and they’re interconnected by edges, also called graphs.

ArangoDB is probably the most popular graph database used today. It was published in 2015 and fits in a number of categories on our site including graph and document databases.

Its core functionality is divided into three parts for document, graph and cluster datasets. Its graph features include pattern matching, distributed graphs and nested properties.

Neo4j is another open-source graph database, but it’s a little older. It was launched in 2007 and utilizes Cypher, a query language described on its site as “the most efficient and expressive way to describe relationship queries.”

While the graph database makes up the Neo4j core, it offers additional products for analytics, data discovery and development. The database’s core features include high availability, online backup and “whiteboard friendly” data modeling.

OrientDB is a relatively young database management solution with support for graph, document, key value and object-oriented database models. It’s open source and supports the Gremlin programming/querying language.

The product’s graph database tools actually supports SQL as well, but other features include JSON libraries, ACID transactions and distributed cluster configuration. An interesting component about this tool, though, is its graph editor for easy visual data manipulation.

Relational, document and graph databases are three of the more common database types available. But others types include object-oriented, operational, key-value and wide-column databases.

Hive is almost a data warehouse, but it has a SQL-like interface to help users query data using the HiveQL language. It’s built atop Apache Hadoop, a big-data processing filesystem.

Some of the core features include a metastore, driver and compiler. It’s typically used to give structure to data already being stored and enabling traditional data mapping.

Elasticsearch fits somewhere between a search engine and a database, but I’m including it since many people use it as a NoSQL datastore. It’s built on Lucene, an information retrieval library from Apache.

Several large companies use it to power datastores and search components such as GitHub, Facebook and Adobe. The tool aggregates large datasets and helps users identify trends and patterns within datasets.

Cassandra is an Apache-developed distributed NoSQL database system that’s been around since 2008. It’s believed to be one of the most scalable database options to choose from because it handles data across many commodity servers.

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The tool was developed at Facebook as an open-source project on Google code. Some features of note are its decentralized structure, replication capabilities and tunable consistency to reduce failover.

Open-Source and Free Database Software