February 2, 2026
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by Devyani Mehta / February 2, 2026
From engineering teams building scalable applications to data leaders powering real-time analytics, the database you rely on can determine performance, reliability, and long-term growth.
When budgets are tight, that often leads teams to evaluate the best free database software as a practical alternative to expensive or overengineered platforms.
I’ve seen organizations struggle with rigid legacy systems just as often as they overcomplicate things by adopting tools they don’t actually need. The reality is that no single database software works for every use case. Some teams need relational databases for structured, transactional data. Others benefit more from document database software for flexible schemas and relationship-heavy data
The good news? Today’s database ecosystem includes mature, production-ready free options across all of these categories. Whether you’re a startup validating ideas, a growing team keeping infrastructure costs in check, or a developer building cloud-native applications, free database tools can deliver serious performance without sacrificing reliability.
Amazon Relational Database Service (RDS): Best for managed cloud databases
For automated backups, scalability, and seamless AWS integration without hands-on infrastructure management
Aerospike: Best for real-time, low-latency workloads
For high-throughput applications, geospatial indexing, and multi-datacenter replication at scale
ArangoDB: Best multi-model database
For handling document, graph, and key-value data in a single platform with flexible querying
Couchbase: Best for NoSQL and distributed apps
For fault-tolerant architectures, flexible data models, and SQL-like querying in NoSQL environments
Dgraph: Best GraphQL-native database
For real-time applications that need fast queries, native GraphQL APIs, and deep relationship traversal
IBM Db2: Best for enterprise relational workloads
For mission-critical transactional and analytical processing with enterprise-grade reliability
InterSystems Caché: Best for mission-critical legacy systems
For high-performance applications in healthcare, finance, and government requiring proven stability
InterSystems IRIS: Best for real-time analytics applications
For building data-intensive, real-time analytics and machine learning-driven applications
MariaDB: Best open-source relational database
For cost-effective, SQL-compatible database management with strong community-driven innovation
MarkLogic: Best for enterprise unstructured data
For managing, searching, and indexing large volumes of structured and unstructured data in one system
Neo4j: Best graph database
For modeling complex relationships, powering graph analytics, and enabling AI-driven insights
ScyllaDB: Best Cassandra-compatible NoSQL database
For high availability and low latency at scale with full Cassandra protocol compatibility
If you feel overwhelmed by the wealth of information about free database software solutions, this comparison table will help you with all the essential aspects:
| Best database software | G2 rating | Free plan | Paid plan |
| Amazon Relational Database Service (RDS) | 4.5/5 ⭐ | Available, limited features | Custom pricing |
| Aerospike | 4.4/5 ⭐ | Free-trial available | From $1.20 onward |
| ArangoDB | 4.6/5 ⭐ | Available, limited features | Custom pricing |
| Couchbase | 4.3/5 ⭐ | Free-trial available | From $0.15 per hour per node |
| Dgraph | 4.7/5 ⭐ | Free open-source plan | From $39.99 per month |
| IBM Db2 | 4.1/5 ⭐ | Available, limited features | From $99 per month |
| InterSystems Caché | 4.3/5 ⭐ | Free-trial available | Custom pricing |
| InterSystems IRIS | 4.5/5 ⭐ | Available, limited features | Custom pricing |
| Maria DB | 4.4/5 ⭐ | Available | Open-source software |
| MarkLogic | 4.3/5 ⭐ | Available, limited features | Custom pricing |
| Neo4j | 4.5/5 ⭐ | Available, limited features | From $65/month onwards |
| ScyllaDB | 4.5/5 ⭐ | Available, limited features | Custom pricing |
*All pricing details mentioned in the article are based on publicly available data at the time of publication and are subject to change.
The demand for modern database management systems continues to rise as organizations generate, process, and rely on data more than ever. From transactional applications and real-time analytics to AI-driven and distributed workloads, databases sit at the core of nearly every digital product and service.
Whether teams are managing customer data, powering large-scale applications, or extracting insights from complex datasets, choosing the right database has become a strategic decision, not just a technical one.
And from what I’ve seen, “best” doesn’t always mean “most complex” or “most expensive.” Some databases excel because they simplify operations, while others stand out by offering flexibility, performance, or specialized data models that better match real-world use cases.
To build this list, I started with G2 data, shortlisting top-rated database platforms based on their G2 scores, market presence, and consistent performance across various related software categories.
From there, I analyzed product documentation and recent, verified G2 user reviews to validate real-world performance and identify where each solution truly excels, or falls short.
The goal was straightforward: understand what each database is best suited for, how it performs in production environments, and which types of teams benefit most from it. I also paid close attention to accessibility factors, such as open-source availability, free tiers, trials, or cloud-managed options, so readers can explore these tools with minimal upfront commitment.
The screenshots featured in this article may include images from the vendor’s G2 profile or publicly available product materials.
Amazon Relational Database Service (RDS) enables users to build, manage, and expand databases in the cloud. It offers scalable capacity while automating time-consuming administrative tasks, including hardware provisioning, setup, patches, and backups.
It frees businesses to focus on services while providing the performance and security they need. Top operational features include the Amazon RDS Management Console, the AWS RDS Command-Line Interface, and straightforward API calls for quick and easy setup.
| Pros of Amazon Relational Database Service |
Cons of Amazon Relational Database Service
|
| Supports a range of database engines |
Limited database support available
|
| Automated backups available |
Difficult to work with large datasets
|
| Strong indexing of data |
Limited customization capability
|
“What I like best about Amazon Relational Database Service (RDS) is its ability to simplify the management of relational databases with automated backups, scaling, and maintenance. This allows users to focus on application development without worrying about the underlying database infrastructure. The seamless integration with other AWS services and robust security features further enhance its appeal.”
- Amazon Relational Database Service (RDS) review, Cuong M.
“As a managed service, RDS may not offer the same level of customization and control as self-managed databases, which can be a limitation for certain advanced use cases.“
- Amazon Relational Database Service (RDS) review, Nireeksha P.
Aerospike is a cloud-based, on-premise NoSQL database platform that enables e-commerce, retail, online gaming, telecoms, and advertising companies to simplify multi-site clustering, cross-datacenter replication, and load balancing, among other processes, on a single platform. It protects data with encryption, authentication, role-based access controls, and website whitelisting.
| Pros of Aerospike |
Cons of Aerospike
|
| Can scale horizontally by adding more nodes to the cluster |
Record size limitations
|
| Geospatial indexing capabilities |
Lack of a proper interface
|
| Professional customer support |
Lack of auditing features
|
"Aerospike helps store data as cached and the database with complete XDR functionality. It's an excellent database by combining the power of Redis and SQL-compliant queries.”
- Aerospike review, Imran K.
"Aerospike can be tricky to size the cluster, although support is beneficial.”
- Aerospike review, Ido B.
ArangoDB is a highly scalable, multi-model database that excels in handling complex, interconnected data structures. As a document database, it's optimized for storing and querying data in a flexible JSON-like format, making it ideal for applications that require rapid development and efficient data management.
| Pros of ArangoDB |
Cons of ArangoDB
|
| Helpful in retrieving data from multiple collections |
Low performance on complex aggregations
|
| Multi-model database |
Unstable user interface
|
| Intuitive Arango query language |
Lacks granularity in access control
|
"The mixture of the document, search, and graph models has made our decisions easier. We can limit our stack to use Arango and not have an explosion of vendor systems for each purpose.”
- ArangoDB review, Kevin B.
"Creating Property graphs is easy. However, there is no direct way to create an RDF/OWL graph. RDF triples are useful in machine learning.”
- ArangoDB review, Amardeep Singh S.
Couchbase is a feature-rich database management system for small and midsize organizations and large corporations across industries such as banking, hotels, energy, information technology (IT), retail, telecommunications, and manufacturing.
Couchbase is a multi-model NoSQL database designed exclusively for mission-critical applications. It’s a document-oriented distributed database that combines two popular NoSQL technologies: Membase and CouchDB.
| Pros of Couchbase |
Cons of Couchbase
|
| Flexible data model |
High memory usage
|
| The architecture ensures fault tolerance |
Complex configuration
|
| Provides NoSQL capabilities |
Poor user experience and learning curve
|
"Easy to get started. We can query the DB using N1QL, which is very similar to SQL, so you don't need extra knowledge to get started. The UI is very clear and easy to understand. Indexing is easy to implement; we can see all available indices, and while running queries, we can see which index was used. Loved this option.”
- Couchbase review, Amit P.
"Adding authorized users was a bit challenging. However, my team figured it out after some poking around."
- Couchbase review, Nico P.
Dgraph is a graph database system with a single schema development model. Users can use the tool to develop a schema, deploy it, and receive fast database and API access without writing any code. Dgraph allows users to choose between GraphQL and DQL, so anyone with no prior knowledge of graph databases to get started.
| Pros of Dgraph | Cons of Dgraph |
| Highly scalable with low latency |
Requires high RAM
|
| Hassle-free data retrieval | Occasional bugs |
| Gives you a production-ready DGraph cluster |
DGraph Query Language (DQL) has a learning curve
|
We have opted for the Dgraph Cloud platform for our enterprise, as it is highly scalable and offers low latency. It's excellent for requirements with real-time transactional workloads, as it effectively synchronizes customer records. Data retrieval is hassle-free & we can perform arbitrary depth joins without worrying about our cluster limitations."
- Dgraph review, Varshini S.
"Dgraph requires high RAM to store a graph compared to other offerings. The managed offering doesn't provide all the functionality possible using its Kubernetes cluster. The management has to be done by yourself or the DevOps team of the organization.”
- Dgraph review, Aditya G.
IBM Db2 is a relational database management system (RDBMS) that efficiently stores, analyzes, and retrieves data. Companies of all sizes use Db2 for transactional and analytical processes as it offers continuous data availability to keep them running smoothly. Db2 also supports NoSQL features, such as XML, graph store, and JSON.
| Pros of IBM Db2 |
Cons of IBM Db2
|
| Suitable for demanding workloads |
Outdated auditing feature
|
| Available on cloud platforms |
Hard to navigate knowledge center
|
| Supports advanced analytical capabilities |
Relies on vendor lock-in
|
"IBM Db2 is a stable platform and integrated relational database management system that leverages high-performance, virtualization, and energy efficiency features. Also, it is supported by different media."
- IBM Db2 review, Sachin D.
"It would be great if we could have support to have a native UI tool to view data and execute queries. The query performance might be slow sometimes for long-running processes.”
- IBM Db2 review, Vignesh V.
InterSystems Caché is a full-featured database system with all the functionality required to run mission-critical applications, including journaling, backup and recovery, and system administration tools, for healthcare, banking and financial services, government, and other industries.
| Pros of InterSystems Caché |
Cons of InterSystems Caché
|
| Ability to handle large datasets |
Complicated to operate
|
| Intuitive data modeling features | Outdated UI |
| Simple storage architecture |
Customization issues
|
"It's a swift and secure database and can communicate with relational access, web pages, and object access.”
- InterSystems Caché review, Eike Scudellari F.
"The Studio editor is a bit outdated, and I feel a lack of general information on the open web.”
- InterSystems Caché review, Andy C.
InterSystems IRIS is a high-performance data management platform that gives IT specialists the tools to develop machine learning and data connectivity applications. The software also supports database administration for SQL and NoSQL databases. It's primarily designed for organizations that want bespoke apps to quickly handle incoming data and perform real-time analytics.
| Pros of InterSystems IRIS |
Cons of InterSystems IRIS
|
| Ability to handle complex queries |
Steep learning curve
|
| Supports multiple data models |
Difficulty in navigating documentation
|
| Robust integration platform, enabling easy data exchange |
Admin portal is difficult to navigate
|
"It's fast, lets you work with many technologies, not just healthcare-related ones, and integrates many cool features into your projects by default. Without doing any extra work, you will get a trace log that lets you search to and redo processes, fixing errors. It includes a fast and flexible database with a tree structure that can also be used with regular SQL."
- InterSystems IRIS review, Jaime L.
"I think the biggest downside to InterSystems Iris (and it is actually small in comparison to what it could be) is that if you want to add custom functionality, you will have to learn the InterSystems-specific programming language (at least a little) to get it built out. It follows pretty standard programming rules and syntax, though, so it won't take long to get moving with it."
- InterSystems IRIS review, Victoria C.
MariaDB relieves businesses of the costs, limitations, and complexity of proprietary databases, allowing them to focus on what matters most: building creative, customer-facing apps. MariaDB employs pluggable, purpose-built storage engines to accommodate workloads that traditionally needed a range of specialist databases.
MariaDB provides unrivaled operational agility without sacrificing critical corporate capabilities, such as genuine ACID compliance and full SQL support.
| Pros of MariaDB |
Cons of MariaDB
|
| Easy import and export of data |
Backend processing limitations
|
| Highly compatible with SQL |
Performance issues with large infrastructure
|
| Community-driven, leading to innovation and improvements |
Hard to find tutorials or community examples
|
"It's a reliable and open-source database system that doesn't worry the users. I used this database over Oracle because of its performance and availability. We can leave an impression on the customers by using the MariaDB database.”
- MariaDB review, Tabassum K.
"It's not convenient for a big stream of data. Further, it performs relatively well in terms of clustering and is constantly updated with new features and functions."
- MariaDB review, Satyam G
MarkLogic is an enterprise-grade NoSQL document database renowned for its ability to handle massive volumes of diverse data, including XML, JSON, and RDF. It offers a unique blend of database, search, and application server functionalities within a single platform.
| Pros of MarkLogic |
Cons of MarkLogic
|
| Multimedia database capabilities |
Limited spreadsheet capabilities
|
| Enterprise search functionality |
Lacks proper search capabilities
|
| Efficiently handles unstructured and diverse data types |
Difficult to work with large datasets
|
“MarkLogic is a database platform managing large dataflows and different datatypes. It also stores structured and unstructured queries, along with dataflows, all of which can be managed under a single device. It helps users index and search large datasets faster and allows them to handle increasing amounts of data. MarkLogic is compliant with the ACID properties of atomicity, isolation, durability, and consistency. MarkLogic can be integrated with various third-party tools and provides confidentiality, integrity, and auditing.”
- MarkLogic review, Harshit L.
“The license cost is extremely high, and so is the amount of space required to store data.”
- MarkLogic review, Abdalla H.
Neo4j is an open-source graph database that helps businesses make data-driven decisions by visualizing relationships among people, processes, and systems. Neo4j maintains interconnected data by default, making data easier to comprehend. Companies can also use the property graph model to develop machine learning and AI models.
| Pros of Neo4j | Cons of Neo4j |
| Helpful in creating your own chatbots | Complex syntax |
| Ample graph formats | Limited graph size |
| Schema-free and index-free database |
Less documentation available
|
“Neo4j is the most interactive and easy-to-use or query tool I have ever worked with. The ciphers are so user-friendly that someone with no programming or query language knowledge can get started at any time, which gives us an edge in explaining BI analysis and parameters to our customers. Visualizations help you debug and resolve issues way faster than other DBs. And their integration with most cloud services allows a smooth integration in our applications.“
- Neo4j review, Gariba G.
“I did not find a lot of resources to help when I got stuck. Also, the setup process was a bit tedious, especially with only the documentation to go off, but I managed to figure out the driver's issues.”
- Neo4j review, Ian J.
ScyllaDB is an open-source distributed NoSQL database. It was created to work with Apache Cassandra while delivering much greater throughputs and reduced latencies. It supports the same protocols and file formats as Cassandra but is a completely rewritten implementation with the C++20 language.
| Pros of ScyllaDB |
Cons of ScyllaDB
|
| Ability to handle increasing workloads |
Quite resource-intensive
|
| Low latency makes it suitable for real-time applications |
Lack of community support
|
| Increased compatibility |
Limited documentation features
|
“We have been utilizing ScyllaDB for a long time now. It is a reliable, highly available NoSQL DB due to its replication. Ensuring that the data remains there even after multiple nodes fail.
Our in-house team got great help from ScyllaDB support while implementing the DB due to its supportability with CQL. Best example of data consistency, reliability, and performance.”
- ScyllaDB review, Chanchala B.
"The setup and configuration complexity of ScyllaDB can be difficult for novices. Furthermore, the documentation sometimes lacks clarity for advanced features."
- ScyllaDB review, Riya V.
Start by matching the database to your workload, not just the feature list. If you’re running transactional or SQL-heavy applications, tools like MariaDB or Amazon RDS (free tier) are easier to adopt. For relationship-heavy or connected data, a graph database like Neo4j makes more sense. Also factor in your team’s experience, some tools save money but require more hands-on management.
Yes, but scaling looks different depending on the database. ScyllaDB and Aerospike are designed to scale horizontally with increasing workloads, while free tiers of managed services may cap storage or throughput.
Most free database tools integrate well at the API or driver level. For example, MariaDB works seamlessly with common web frameworks, while Neo4j integrates easily with cloud services and analytics tools. That said, managed integrations and native connectors are often limited in free versions.
Open-source databases like MariaDB and ScyllaDB give you full control and customization but require you to manage infrastructure and updates. Cloud-based options, such as Amazon RDS, handle maintenance for you but typically restrict resources or features unless you upgrade.
Start by matching the database to your workload, not just the feature list. If you’re running transactional or SQL-heavy applications, tools like MariaDB or Amazon RDS (free tier) are easier to adopt. For relationship-heavy or connected data, a graph database like Neo4j makes more sense.
Yes, but scaling looks different depending on the database. ScyllaDB and Aerospike are designed to scale horizontally with increasing workloads, while free tiers of managed services like Amazon RDS may cap storage or throughput. Always check whether scaling requires upgrading to a paid plan or adding infrastructure yourself.
Most free database tools integrate well at the API or driver level. For example, MariaDB works seamlessly with common web frameworks, while Neo4j integrates easily with cloud services and analytics tools. That said, managed integrations and native connectors are often limited in free versions.
Open-source databases like MariaDB and ScyllaDB give you full control and customization but require you to manage infrastructure and updates. Cloud-based options, such as Amazon RDS, handle maintenance for you but typically restrict resources or features unless you upgrade. The right choice depends on how much control your team wants versus how much operational work you can handle.
Migration between similar systems is usually straightforward. Moving from MySQL to MariaDB is often seamless, while switching to a graph database like Neo4j may require rethinking your data model. Many tools offer import utilities, but complex schemas or large datasets may still need manual tuning.
Migration between similar systems is usually straightforward. Moving from MySQL to MariaDB is often seamless, while switching to a graph database like Neo4j may require rethinking your data model. Many tools offer import utilities, but complex schemas or large datasets may still need manual tuning.
Understanding your data is essential for building reliable, high-performing applications and making informed business decisions. The free database software I evaluated above offers a strong starting point for storing, managing, and analyzing data without upfront costs. I hope this list of the best free database software helps you find the right solution for your specific workload and growth goals.
Once your data is in place, the best AI agents for business operations can help you automate workflows and streamline decision-making.
This article was originally published in 2023. It has been updated with new information.
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Devyani Mehta is a content marketing specialist at G2. She has worked with several SaaS startups in India, which has helped her gain diverse industry experience. At G2, she shares her insights on complex cybersecurity concepts like web application firewalls, RASP, and SSPM. Outside work, she enjoys traveling, cafe hopping, and volunteering in the education sector. Connect with her on LinkedIn.
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