Best Database Software in China - Page 9

Zoho Tables provides a unified teamwork solution by connecting people, processes and information. Our mobile app allows you to stay on top of all your tasks, wherever you are. This ensures productivity on the move! Many software users are caught between tools that are too complex and those lacking essential features. You can create your own solutions to meet your unique needs with Zoho Tables without having to write a single line code. Zoho Tables is unique in its versatility. You can view your data in five different ways: Grid, Kanban (a system of numbered cards), Calendar, Gallery and Form.

Articulate your prompt clearly, specify the necessary tables, and create a query utilizing your preferred AI model. You can establish numerous connections as needed while benefiting from autocomplete functionality for SQL queries, enhancing your efficiency. We ensure the confidentiality of your schemas, queries, and credentials; the data you share is solely used for crafting SQL queries. You can easily download your outputs in CSV format and visualize them through graphs and charts. Discover the capabilities of AI-enhanced SQL queries with our complimentary plan, allowing you to swiftly construct intricate SQL queries with AI assistance. SQLPilot serves as your primary tool for generating context-rich SQL queries seamlessly. Enjoy a streamlined experience as you navigate through your data and queries with ease.

Entity Framework (EF) Core is a versatile, lightweight, and open-source version of the widely used Entity Framework data access technology that operates across different platforms. It empowers .NET developers to interact with databases through .NET objects, significantly reducing the amount of data-access code that would typically need to be written. In EF Core, data interaction occurs through a model, which consists of entity classes and a context object that acts as a connection to the database. This context object facilitates both querying and data manipulation. Developers can generate a model directly from an existing database or manually create one to correspond with the database schema. After establishing a model, EF migrations can be employed to build a database from it, allowing for the database to evolve in tandem with any changes made to the model. Furthermore, instances of entity classes can be retrieved from the database using Language Integrated Query (LINQ), and operations such as creating, deleting, and modifying records in the database are accomplished through these instances, thus streamlining the data management process. Overall, EF Core simplifies database interactions and enhances the efficiency of data-driven applications.

Optimize your time and reduce expenses by simplifying data pipelines using hassle-free open source solutions. Covering everything from data ingestion to visualization, all components are seamlessly integrated, fully managed, and exceptionally reliable, ensuring your engineering team enjoys working with data. You can opt for any of DoubleCloud’s managed open source services or take advantage of the entire platform's capabilities, which include data storage, orchestration, ELT, and instantaneous visualization. We offer premier open source services such as ClickHouse, Kafka, and Airflow, deployable on platforms like Amazon Web Services or Google Cloud. Our no-code ELT tool enables real-time data synchronization between various systems, providing a fast, serverless solution that integrates effortlessly with your existing setup. With our managed open-source data visualization tools, you can easily create real-time visual representations of your data through interactive charts and dashboards. Ultimately, our platform is crafted to enhance the daily operations of engineers, making their tasks more efficient and enjoyable. This focus on convenience is what sets us apart in the industry.

LanceDB is an accessible, open-source database specifically designed for AI development. It offers features such as hyperscalable vector search and sophisticated retrieval capabilities for Retrieval-Augmented Generation (RAG), along with support for streaming training data and the interactive analysis of extensive AI datasets, making it an ideal foundation for AI applications. The installation process takes only seconds, and it integrates effortlessly into your current data and AI toolchain. As an embedded database—similar to SQLite or DuckDB—LanceDB supports native object storage integration, allowing it to be deployed in various environments and efficiently scale to zero when inactive. Whether for quick prototyping or large-scale production, LanceDB provides exceptional speed for search, analytics, and training involving multimodal AI data. Notably, prominent AI companies have indexed vast numbers of vectors and extensive volumes of text, images, and videos at a significantly lower cost compared to other vector databases. Beyond mere embedding, it allows for filtering, selection, and streaming of training data directly from object storage, thereby ensuring optimal GPU utilization for enhanced performance. This versatility makes LanceDB a powerful tool in the evolving landscape of artificial intelligence.

Tobiko is an advanced data transformation platform designed to accelerate data delivery while enhancing efficiency and minimizing errors, all while maintaining compatibility with existing databases. It enables developers to create a development environment without the need to rebuild the entire Directed Acyclic Graph (DAG), as it smartly alters only the necessary components. When a new column is added, there's no requirement to reconstruct everything; the modifications you've made are already in place. Tobiko allows for instant promotion to production without requiring you to redo any of your previous work. It eliminates the hassle of debugging complex Jinja templates by allowing you to define your models directly in SQL. Whether at a startup or a large enterprise, Tobiko scales to meet the needs of any organization. It comprehends the SQL you create and enhances developer efficiency by identifying potential issues during the compilation process. Additionally, comprehensive audits and data comparisons offer validation, ensuring the reliability of the datasets produced. Each modification is carefully analyzed and categorized as either breaking or non-breaking, providing clarity on the impact of changes. In the event of errors, teams can conveniently roll back to previous versions, effectively minimizing production downtime and maintaining operational continuity. This seamless integration of features makes Tobiko not only a tool for data transformation but also a partner in fostering a more productive development environment.

Tembo is an intelligent AI teammate that automates engineering workflows by handling error detection, code crafting, and database optimization so developers can focus on building new features. It continuously monitors production systems and automatically converts errors into pull requests, streamlining the debugging process without manual intervention. Tembo also enhances database performance by finding and fixing slow queries and missing indexes in PostgreSQL and Supabase environments. Through integrations with popular platforms like GitHub, GitLab, Jira, and Linear, Tembo transforms tickets and error logs into working code, accelerating sprint planning and issue resolution. Its code explorer analyzes your entire codebase to identify technical debt, security vulnerabilities, and refactoring opportunities, helping maintain code quality. Upcoming features include backlog prioritization and personalized solutions that align with your team’s culture and practices. Users report significant gains in engineering velocity and productivity after adopting Tembo. Setting up the platform is quick and easy, enabling teams to automate routine tasks within minutes.

Impala offers rapid response times and accommodates numerous concurrent users for business intelligence and analytical inquiries within the Hadoop ecosystem, supporting technologies such as Iceberg, various open data formats, and multiple cloud storage solutions. Additionally, it exhibits linear scalability, even when deployed in environments with multiple tenants. The platform seamlessly integrates with Hadoop's native security measures and employs Kerberos for user authentication, while the Ranger module provides a means to manage permissions, ensuring that only authorized users and applications can access specific data. You can leverage the same file formats, data types, metadata, and frameworks for security and resource management as those used in your Hadoop setup, avoiding unnecessary infrastructure and preventing data duplication or conversion. For users familiar with Apache Hive, Impala is compatible with the same metadata and ODBC driver, streamlining the transition. It also supports SQL, which eliminates the need to develop a new implementation from scratch. With Impala, a greater number of users can access and analyze a wider array of data through a unified repository, relying on metadata that tracks information right from the source to analysis. This unified approach enhances efficiency and optimizes data accessibility across various applications.

Instant is designed to facilitate the creation of applications that function seamlessly in both real-time and offline environments. It simplifies the process of developing collaborative tools akin to Notion or Figma. Today’s top applications share a set of crucial features, including immediate interactions, minimal loading screens, effortless collaboration, and reliable performance even without an internet connection. Instant addresses these challenges by providing a browser-accessible database that users can subscribe to directly. When you incorporate relational queries into your application, we take care of the backend complexities. The inception of Instant came from the understanding that many intricate user interface challenges are fundamentally related to database issues. By tackling these problems at the database level, the resulting software becomes not only more robust but also more streamlined. Ideally, when applications function optimally, any adjustment made by a user should be visible immediately, minimizing the need for spinners, loading indicators, or refresh buttons. With Instant, the management of optimistic updates is automated, enhancing user experience further. Ultimately, this approach empowers developers to focus more on innovation rather than the intricacies of data management.

HarperDB is an innovative platform that integrates database management, caching, application development, and streaming capabilities into a cohesive system. This allows businesses to efficiently implement global-scale back-end services with significantly reduced effort, enhanced performance, and cost savings compared to traditional methods. Users can deploy custom applications along with pre-existing add-ons, ensuring a high-throughput and ultra-low latency environment for their data needs. Its exceptionally fast distributed database offers vastly superior throughput rates than commonly used NoSQL solutions while maintaining unlimited horizontal scalability. Additionally, HarperDB supports real-time pub/sub communication and data processing through protocols like MQTT, WebSocket, and HTTP. This means organizations can leverage powerful data-in-motion functionalities without the necessity of adding extra services, such as Kafka, to their architecture. By prioritizing features that drive business growth, companies can avoid the complexities of managing intricate infrastructures. While you can’t alter the speed of light, you can certainly minimize the distance between your users and their data, enhancing overall efficiency and responsiveness. In doing so, HarperDB empowers businesses to focus on innovation and progress rather than getting bogged down by technical challenges.

Facilitate rapid transactions to minimize customer churn, no matter their location. Build web applications that boast low latency, enabling users to enjoy instantaneous interactions and real-time updates. Implement managed sharding to provide data isolation, alleviate noisy neighbor issues, and comply with geographical data residency standards. Offer ultra-low latency API services globally with well-placed data centers to ensure swift response times. Access your worldwide database through a single endpoint, with connections directed to the nearest replica. Seamlessly import your existing Postgres database clusters and expand them globally using Fortress. Let our proxy manage sharing within the application to fulfill your performance needs and geographical data residency requirements. Developers rely on Fortress to cut down network latency for users around the world, adhere to data sovereignty laws, all while benefiting from a platform that effectively handles horizontal scalability. This approach not only enhances user satisfaction but also streamlines operational efficiency across diverse markets.

Turso is a distributed database service compatible with SQLite, designed to ensure low-latency data access for various environments, including online, offline, and on-device platforms. Built on the foundation of libSQL, which is an open-source variant of SQLite, Turso allows developers to position databases in proximity to their users, thereby boosting application performance significantly. It offers easy integration with a wide range of frameworks, languages, and infrastructure providers, which streamlines data management for applications that utilize large language models and AI agents. Among its many features, Turso includes unlimited databases, the ability to instantly roll back changes with branching, and advanced native vector search capabilities at scale, enabling effective parallel searches across different users, instances, or contexts using SQL database integration. The platform places a strong emphasis on security, implementing encryption for data both at rest and during transmission, while also adopting an API-first approach that simplifies programmatic database management. Additionally, Turso's architecture supports rapid scaling to meet the demands of growing applications, making it a versatile choice for developers in today's data-driven landscape.

MySQLTuner is a lightweight script written in Perl, aimed at helping database administrators enhance the performance and configuration of MySQL and MariaDB systems. It evaluates essential metrics and parameters associated with system performance, security, and resource consumption, offering practical suggestions for improvement. By analyzing the existing workload, cache utilization, query efficiency, and memory allocation, MySQLTuner pinpoints possible bottlenecks and recommends modifications to configuration settings. This tool is especially beneficial for continuous maintenance, as it draws attention to problems like inefficient indexing, the use of too many temporary tables, or poor query caching practices. Database administrators rely on MySQLTuner not only to ensure peak performance but also to minimize system overhead while fostering a robust and efficient database setup. Its user-friendly interface and straightforward recommendations make it an indispensable asset for managing databases effectively.

PeeringDB serves as a freely accessible, community-driven repository of networking information, making it the primary source for interconnection details. It plays a crucial role in facilitating the global connections among networks at Internet Exchange Points (IXPs), data centers, and other interconnection venues, acting as an essential resource for making informed interconnection choices. Operated as a non-profit initiative by volunteers, PeeringDB aims to foster the ongoing growth of the Internet. Users have the capability to search through and update the PeeringDB database via a web interface or API, which allows for seamless integration into their custom tools. In addition, PeeringDB provides peeringdb-py as a reference for creating a local cache of its data, promoting the use of this or similar tools to help users stay within API query limits. Furthermore, PeeringDB offers a dataset in .KMZ format that includes geographical coordinates for various interconnection facilities, enhancing accessibility for its users. This focus on user collaboration and data availability strengthens the overall interconnection ecosystem within the Internet.

easyAsPieDB offers a powerful, customizable solution for storing and managing a wide range of data, whether you're tracking books, movies, business tasks, or even your home inventory. Designed for simplicity, no technical skills are required to use the app’s intuitive interface. It operates locally, ensuring that your data remains private and secure with integrated encryption and reliability based on SQLite. The app supports a variety of building blocks, such as text, numbers, dates, barcodes, and drawings, allowing you to organize information in whatever way suits your needs. Power users can leverage advanced features like custom calculations, user-defined formulas, and record relationships to manage more complex data, such as cross-referencing, many-to-one, and one-to-many relationships. Additionally, the app includes data sync capabilities, ensuring you can keep your information up-to-date across devices.

SQLPro Studio is a comprehensive, cross-platform tool designed for database management that operates natively. It accommodates a variety of database systems and comes with numerous features such as syntax highlighting, SQL autocompletion, customizable themes, and a tabbed interface for handling multiple queries at once. Moreover, it includes support for cloud services like Amazon RDS, Microsoft Azure, and Heroku, in addition to SSH tunneling and master password protection to enhance security measures. Performance and user experience are key focuses of SQLPro Studio, which features an intuitive interface that operates without Java, resulting in quicker and more reliable functionality. Users can run several queries simultaneously, with results displayed concurrently, including any errors and messages that arise. SQLPro is designed to cater to both simple and complex database requirements, ensuring that everything is easily accessible for users. Overall, it stands out as a versatile solution for anyone looking to manage databases efficiently.

Apache DataFusion is a versatile and efficient query engine crafted in Rust, leveraging Apache Arrow for its in-memory data representation. It caters to developers engaged in creating data-focused systems, including databases, data frames, machine learning models, and real-time streaming applications. With its SQL and DataFrame APIs, DataFusion features a vectorized, multi-threaded execution engine that processes data streams efficiently and supports various partitioned data sources. It is compatible with several native formats such as CSV, Parquet, JSON, and Avro, and facilitates smooth integration with popular object storage solutions like AWS S3, Azure Blob Storage, and Google Cloud Storage. The architecture includes a robust query planner and an advanced optimizer that boasts capabilities such as expression coercion, simplification, and optimizations that consider distribution and sorting, along with automatic reordering of joins. Furthermore, DataFusion allows for extensive customization, enabling developers to incorporate user-defined scalar, aggregate, and window functions along with custom data sources and query languages, making it a powerful tool for diverse data processing needs. This adaptability ensures that developers can tailor the engine to fit their unique use cases effectively.

TaffyDB is a JavaScript library that is open source and integrates robust database functionalities into JavaScript applications. With its compact file size, it ensures rapid query performance while offering a data selection engine that is designed with JavaScript in mind. The library provides features akin to traditional databases, such as counting, updating, and inserting records, all while ensuring strong compatibility across different web browsers. Its design allows for easy extension through custom functions and seamless integration with any DOM library, as well as server-side JavaScript environments. Setting up a database is a simple process; users can create an empty database, one with a single object, an array, or even a JSON string. After establishing a database, you can execute queries by invoking the root function and constructing filter objects to refine your search. TaffyDB enables filtering based on database names and object comparisons, facilitating easy data access and dynamic modifications. Additionally, the use of custom functions grants users comprehensive control over query outcomes, enhancing the overall flexibility and power of the library in various applications. This versatility makes TaffyDB an excellent choice for developers seeking to implement database-like capabilities directly in their JavaScript projects.

Oracle Autonomous Database is a cloud-based database solution that automates various management tasks, such as tuning, security, backups, and updates, through the use of machine learning, thereby minimizing the reliance on database administrators. It accommodates an extensive variety of data types and models, like SQL, JSON, graph, geospatial, text, and vectors, which empowers developers to create applications across diverse workloads without the necessity of multiple specialized databases. The inclusion of AI and machine learning features facilitates natural language queries, automatic data insights, and supports the creation of applications that leverage artificial intelligence. Additionally, it provides user-friendly tools for data loading, transformation, analysis, and governance, significantly decreasing the need for intervention from IT staff. Furthermore, it offers versatile deployment options, which range from serverless to dedicated setups on Oracle Cloud Infrastructure (OCI), along with the alternative of on-premises deployment using Exadata Cloud@Customer, ensuring flexibility to meet varying business needs. This comprehensive approach streamlines database management and empowers organizations to focus more on innovation rather than routine maintenance.

Convex is a reactive backend platform that is open-source and allows developers to create full-stack applications solely using TypeScript. This platform features a document-relational database that employs TypeScript for writing queries and mutations, thereby promoting type safety and fostering smooth integration with frontend components. With Convex, real-time synchronization is automatically managed between the frontend, backend, and database states, removing the need for developers to handle state management, cache invalidation, or WebSockets manually. Additionally, it provides in-built functionalities such as cloud functions, scheduling, authentication, file storage, and an array of components that can be easily integrated using a simple npm install command. Developers have the capability to define their entire backend through code, encompassing database schemas, queries, and APIs, all of which benefit from type-checking and autocompletion, while AI can assist in generating code with remarkable precision. The architecture of Convex guarantees that all transactions are serializable, ensuring strong consistency and effectively eliminating race conditions. Overall, this platform simplifies backend development while enhancing developer productivity through its comprehensive TypeScript support.

ChartDB is a versatile, open-source tool for web-based database diagramming that quickly generates visual representations of your schema, accommodating various popular database management systems such as PostgreSQL, MySQL, SQL Server, SQLite, ClickHouse, and Oracle, or even from a single query without the need for complex configurations or database access. Users can interactively modify diagrams through a drag-and-drop interface, incorporate annotations, and tailor relationships as needed, with the option to export clear, SQL DDL scripts specific to different dialects or share diagrams as images. Enhancing productivity, ChartDB Cloud introduces features such as real-time collaboration, live cursors, team avatars, and synchronized edits, along with an automatic save functionality to keep your work secure. Additionally, the platform's AI assistant boosts efficiency by identifying missing relationships, proposing foreign keys, and recommending schema improvements with just one click. Furthermore, diagrams are kept up to date through automated schema synchronization using a secure syncer CLI, making it particularly beneficial for continuous integration and deployment pipelines while maintaining the layout and styling as your data model changes. This ensures that teams can collaborate effectively and adapt to modifications in their database structures seamlessly.

Teable is a no-code application and database builder driven by AI, enabling users to seamlessly convert documents, spreadsheets, and unstructured data into dynamic databases, applications, automations, and workflows with ease. The platform fosters real-time collaboration while featuring advanced permissions (team synchronization) and authority matrices to ensure data governance and security. Users can create various representations of their data such as Kanban boards, calendars, galleries, forms, and grids, while also being able to connect and manage millions of rows without any decline in performance. Additionally, it offers robust dashboard analytics and automated workflows, which include triggers and condition-based actions, along with features like undo/redo/history, validation, linking, sorting, filtering, and formulas, empowering users to not only analyze but also take action on their data. Furthermore, Teable supports a range of AI models, including OpenAI, Claude, DeepSeek, and self-hosted LLMs, to facilitate intelligent data processing, and it also supports integrations with SQL databases or direct physical database connections. This comprehensive functionality makes Teable an invaluable tool for businesses looking to enhance their data management capabilities and streamline their operations.

Tiger Data reimagines PostgreSQL for the modern era — powering everything from IoT and fintech to AI and Web3. As the creator of TimescaleDB, it brings native time-series, event, and analytical capabilities to the world’s most trusted database engine. Through Tiger Cloud, developers gain access to a fully managed, elastic infrastructure with auto-scaling, high availability, and point-in-time recovery. The platform introduces core innovations like Forks (copy-on-write storage branches for CI/CD and testing), Memory (durable agent context and recall), and Search (hybrid BM25 and vector retrieval). Combined with hypertables, continuous aggregates, and materialized views, Tiger delivers the speed of specialized analytical systems without sacrificing SQL simplicity. Teams use Tiger Data to unify real-time and historical analytics, build AI-driven workflows, and streamline data management at scale. It integrates seamlessly with the entire PostgreSQL ecosystem, supporting APIs, CLIs, and modern development frameworks. With over 20,000 GitHub stars and a thriving developer community, Tiger Data stands as the evolution of PostgreSQL for the intelligent data age.

MongoLime provides a user-friendly platform for overseeing and managing MongoDB connections effectively. It enables users to view and handle documents, along with accessing statistics, indexes, and various operations. With its intuitive editor, users can create and modify documents seamlessly, while a raw JSON editor is available for more intricate document requirements. The query builder facilitates easy document searches, and users can save their searches for quick retrieval. Additionally, databases and collections can be exported in a JSON format compressed as a ZIP file. Designed specifically for mobile devices and tablets operating on Android, MongoLime’s interfaces ensure effortless management of data collection. Furthermore, the application supports direct connections to MongoDB databases or connections in the Replica Set mode for enhanced flexibility.

There are various strategies to reduce costs within an IT department, but one of the most effective and insightful approaches is to enhance employee productivity. By adopting streamlined work practices, organizations can ensure ongoing savings and improvements. Kal Admin is an essential tool utilized by numerous Analysts, Developers, QAs, and DBAs within Israel's public sector. The software features a Data Dictionary, which serves as a central repository for Business Analysts to document the definitions and descriptions of data elements crucial for fulfilling user requirements, and it also accommodates business terminology. This Dictionary plays a vital role in the subsequent development of database tables. With Kal Admin, users can outline tables without needing to create them in the database immediately, as the columns are specified through the Data Dictionary. Once these defined tables successfully clear quality assurance checks, they can be constructed in the database with just a single click, greatly simplifying the process. Ultimately, this efficiency not only reduces costs but also enhances overall project delivery in the IT sector.