List of the Top 12 Database Software for JSON in 2025

QuerySurge serves as an intelligent solution for Data Testing that streamlines the automation of data validation and ETL testing across Big Data, Data Warehouses, Business Intelligence Reports, and Enterprise Applications while incorporating comprehensive DevOps capabilities for ongoing testing. Among its various use cases, it excels in Data Warehouse and ETL Testing, Big Data (including Hadoop and NoSQL) Testing, and supports DevOps practices for continuous testing, as well as Data Migration, BI Report, and Enterprise Application/ERP Testing. QuerySurge boasts an impressive array of features, including support for over 200 data stores, multi-project capabilities, an insightful Data Analytics Dashboard, a user-friendly Query Wizard that requires no programming skills, and a Design Library for customized test design. Additionally, it offers automated business report testing through its BI Tester, flexible scheduling options for test execution, a Run Dashboard for real-time analysis of test processes, and access to hundreds of detailed reports, along with a comprehensive RESTful API for integration. Moreover, QuerySurge seamlessly integrates into your CI/CD pipeline, enhancing Test Management Integration and ensuring that your data quality is constantly monitored and improved. With QuerySurge, organizations can proactively uncover data issues within their delivery pipelines, significantly boost validation coverage, harness analytics to refine vital data, and elevate data quality with remarkable efficiency.

StarfishETL functions as a Cloud iPaaS solution, enabling the seamless integration of virtually any application with another, provided that both have an accessible API. This capability empowers StarfishETL users to exercise full control over their data initiatives, allowing them to establish distinctive and scalable data connections tailored to their specific needs. By facilitating such flexibility, StarfishETL enhances the overall efficiency of data management and integration processes for its clients.

Manticore Search, introduced in 2017, is an open-source database that evolved from the Sphinx Search engine, integrating its most effective features while significantly improving its functionality and addressing numerous issues through a near-total codebase rewrite, all while adhering to our open-source values. This comprehensive overhaul has transformed Manticore Search into a contemporary, efficient, lightweight, and adaptable database that shines in its full-text search capabilities. We believe that simplifying technology should be a primary focus for vendors in today's market. Our goal is to enable all users, from developers to DevOps professionals, to utilize Manticore products without needing extensive database or search engine expertise, making advanced qualifications unnecessary. Recognizing the value of your time, we strive to minimize the annoyance of lengthy trials that often accompany understanding the impact of various settings on functionalities. Consequently, Manticore Search is engineered to operate effectively with its default settings in most scenarios, ensuring users have a seamless experience right from the outset. By prioritizing user-friendliness, we aim to empower our community to harness the full potential of Manticore Search with ease.

The database interface empowers users to collaboratively view, modify, and visualize their data without requiring extensive knowledge of database systems. It fosters shared authority among teams, ensuring that no single entity monopolizes the control over data management. Users can effortlessly handle queries, columns, rows, tables, and schemas without needing to write any SQL code, making the process as straightforward as working on a spreadsheet, which enhances teamwork and productivity. The days of dealing with scattered snippets and complicated SQL blocks are over, as everything can be neatly organized in one centralized location. Team members are encouraged to share their queries, which helps to prevent redundant efforts and promotes collaboration. This platform provides the most user-friendly way to engage with your data, eliminating the need to write even a single line of SQL code. Outerbase integrates smoothly with a variety of popular databases, enabling quick access to schemas, tables, and columns while reducing the need to switch between different contexts, all through an intuitive user interface designed for simplicity. It also accommodates complex data types, such as JSON, timestamps, and ENUMs, offering users a straightforward experience even when managing intricate data structures. Users can further enhance their queries by embedding variables to create dynamic and adaptable outputs, and they can design eye-catching dashboards in just a few clicks. This approach not only streamlines data management but also makes it visually engaging and accessible to all users involved, ultimately transforming the way teams interact with their data.

Apache DataFusion is a highly adaptable and capable query engine developed in Rust, which utilizes Apache Arrow for efficient in-memory data handling. It is intended for developers who are working on data-centric systems, including databases, data frames, machine learning applications, and real-time data streaming solutions. Featuring both SQL and DataFrame APIs, DataFusion offers a vectorized, multi-threaded execution engine that efficiently manages data streams while accommodating a variety of partitioned data sources. It supports numerous native file formats, including CSV, Parquet, JSON, and Avro, and integrates seamlessly with popular object storage services such as AWS S3, Azure Blob Storage, and Google Cloud Storage. The architecture is equipped with a sophisticated query planner and an advanced optimizer, which includes features like expression coercion, simplification, and distribution-aware optimizations, as well as automatic join reordering for enhanced performance. Additionally, DataFusion provides significant customization options, allowing developers to implement user-defined scalar, aggregate, and window functions, as well as integrate custom data sources and query languages, thereby enhancing its utility for a wide range of data processing scenarios. This flexibility ensures that developers can effectively adjust the engine to meet their specific requirements and optimize their data workflows.

TaffyDB is an open-source JavaScript library that incorporates powerful database features into JavaScript applications. Its lightweight design guarantees fast query execution and includes a data selection engine optimized for JavaScript use. The library replicates functionalities found in conventional databases, such as the ability to count, update, and insert records, while maintaining compatibility across a variety of web browsers. It allows for straightforward expansion through custom functions and can be easily integrated with any DOM library or server-side JavaScript environment. Users can quickly set up a database, whether creating an empty one, initializing it with a single object, utilizing an array, or importing a JSON string. Once the database is set up, queries can be performed by calling the root function and creating filter objects to narrow down searches. TaffyDB supports filtering based on database names and object comparisons, which streamlines data retrieval and modification processes. The inclusion of custom functions empowers users with extensive control over the results of their queries, significantly enhancing the library’s adaptability and utility in a range of applications. Overall, TaffyDB stands out as a fantastic option for developers looking to introduce database-like functions directly into their JavaScript implementations, making it both powerful and versatile. Furthermore, its ease of use ensures that developers of all skill levels can take advantage of its capabilities without facing significant hurdles.

Oracle Autonomous Database represents a cloud-based solution that automates numerous management functions, including tuning, security, backups, and updates, leveraging machine learning to reduce dependency on database administrators. This platform supports a wide array of data types and structures, such as SQL, JSON, graph, geospatial, text, and vectors, which enables developers to build applications suitable for various workloads without needing multiple specialized databases. The integration of AI and machine learning capabilities fosters natural language querying, automatic insights generation, and aids in developing applications that harness the power of artificial intelligence. Moreover, it features intuitive tools for data loading, transformation, analysis, and governance, significantly lessening the need for IT staff involvement. The database also boasts flexible deployment options, from serverless configurations to dedicated arrangements on Oracle Cloud Infrastructure (OCI), as well as the possibility of on-premises deployment through Exadata Cloud@Customer, thereby providing adaptability to meet different business requirements. This all-encompassing strategy not only streamlines database management but also allows organizations to concentrate their efforts more on innovation and less on routine upkeep, enhancing overall operational efficiency. As a result, businesses can leverage advanced technologies while minimizing administrative burdens.

Bytebase is an innovative online platform that fosters collaboration among DBAs and developers, enabling them to efficiently manage the entire database development lifecycle. It empowers users to standardize database modifications through peer reviews, establish linting rules, and seamlessly integrate with GitOps methodologies. The web-based integrated development environment (IDE) allows for the execution of ad-hoc SQL queries while prioritizing data privacy. By streamlining administrative tasks and ensuring thorough policy control, Bytebase helps maintain compliance across various operations. The platform further improves deployment processes by guiding database changes from non-production to production environments with a structured review workflow and optional GitOps integration. It includes over 100 lint rules designed to detect SQL anti-patterns and encourage a uniform SQL style organization-wide. Additionally, users can batch change multiple databases across different environments and tenants within a single ticket, enhancing efficiency. Developers can utilize existing workflows while managing change scripts through version control systems. Bytebase's lockless schema change functionality dramatically minimizes database downtime, reducing it from hours to just seconds. Moreover, Bytebase employs a proactive security strategy that protects your data with measures like access control, data anonymization, watermarking, and detailed audit logging, ensuring robust safeguards against potential threats. This extensive array of features not only boosts productivity but also strengthens the overall integrity and reliability of database management practices, making it an indispensable tool for modern development teams. Ultimately, Bytebase stands out as a comprehensive solution that addresses the evolving needs of database professionals.

Oracle Real Application Clusters (RAC) is a unique and robust database architecture that provides exceptional availability and scalability for both read and write operations across a wide range of workloads, including OLTP, analytics, AI data, SaaS applications, JSON, batch processing, text, graph data, IoT, and in-memory tasks. It efficiently manages complex applications, such as those from SAP, Oracle Fusion Applications, and Salesforce, while ensuring outstanding performance. By employing a specialized fused cache shared among servers, Oracle RAC guarantees rapid local data access, resulting in low latency and high throughput for various data needs. The architecture's capability to parallelize workloads across multiple CPUs enhances overall throughput, and Oracle's advanced storage solutions allow for seamless online expansion of storage. Unlike traditional databases that depend on public cloud infrastructure, sharding, or read replicas to improve scalability, Oracle RAC distinguishes itself by delivering top-tier performance with minimal latency and maximum throughput right from the outset. Additionally, this architecture is crafted to adapt to the shifting requirements of contemporary applications, rendering it a forward-thinking solution for businesses aiming for longevity and efficiency in their database operations. Its design not only ensures reliability but also positions organizations to tackle future challenges in data management effectively.

The connection between your browser and DbNinja is secured through encryption, guaranteeing that your communications are kept private and safe from eavesdropping, even in the absence of SSL. DbNinja is an advanced web application specifically tailored for the management and development of MySQL databases. This platform is invaluable for users needing remote access to their servers from various locations. It boasts a full suite of modern features, including triggers, events, views, stored routines, and foreign keys, while also enabling functionalities like data imports, backups, and user management. With its modern and user-friendly interface, DbNinja works seamlessly across all contemporary browsers on different operating systems. There’s no requirement for registration or payment information, allowing for an effortless experience free from hidden stipulations. Anticipated premium features such as scheduled backups and server monitoring will likely be rolled out soon. Serving as a comprehensive resource for both beginner and advanced MySQL developers, DbNinja enjoys broad compatibility with most shared hosting providers, making it an easily reachable option for many users. This user-friendly aspect allows individuals to effectively manage their databases with confidence and ease. Ultimately, DbNinja significantly improves the overall experience of database management for its users.

Access the newest features and official versions of MongoDB that guarantee full compatibility with the platform. When your cluster faces higher demand, you can effortlessly scale up by adding new servers or boosting the capacity of existing ones within mere minutes. Concentrate on advancing your project while we take care of the backend aspects of your database, including software backups, monitoring, fault tolerance, and updates to keep your system running smoothly. Clusters operating on MongoDB version 4.0 or later can activate sharding, enabling the addition and configuration of individual shards to enhance performance. Every connection to the database management system is safeguarded with TLS encryption, and backups are secured through GPG encryption for added protection. Your data adheres to local regulations, GDPR, and ISO industry standards, ensuring its security and confidentiality. In contrast to conventional databases that rely on standard tables, MongoDB structures data in collections of JSON-like documents, offering significant advantages for projects where data schemas may change over time. This adaptability allows developers to modify their applications with minimal rework, fostering innovation and efficiency in your development process. As your project grows, this approach can lead to both time and cost savings, making MongoDB a valuable asset for any evolving application.

SchemaFlow represents a groundbreaking solution designed to elevate AI-centric development by offering instantaneous access to PostgreSQL database schemas through the Model Context Protocol (MCP). This tool enables developers to connect their databases seamlessly, visualize schema designs with dynamic diagrams, and export schemas in various formats such as JSON, Markdown, SQL, and Mermaid. With built-in support for MCP via Server-Sent Events (SSE), SchemaFlow ensures effortless integration with AI-Integrated Development Environments (AI-IDEs) like Cursor, Windsurf, and VS Code, thereby providing AI assistants with the most up-to-date schema information for accurate code generation. Additionally, it features secure token-based authentication for MCP connections, automatic updates to schemas to keep AI assistants informed of any changes, and an intuitive schema browser that simplifies the navigation of tables and their relationships. By incorporating these functionalities, SchemaFlow not only boosts the productivity of development workflows but also guarantees that AI tools are always working with the latest database data, which is crucial for maintaining high-quality code outputs. Ultimately, this innovative approach enhances collaboration between developers and AI systems, paving the way for more efficient software development practices.