Business Software for DuckDB

DbVisualizer is a universal database client for anyone who works with data, from solo developers and startups to professional teams managing complex environments, including developers, DBAs, analysts, and data engineers working with relational and NoSQL databases. It offers a graphical interface for database development, SQL querying, and data exploration. Key features: - SQL editor with autocomplete, visual query builders, variables, and execution tools - AI Assistant for questions, error explanations, and code analysis - Built-in Git integration for SQL scripts and collaboration - Customizable layouts, key bindings, and UI themes - Favorite scripts and database objects for quick access - Configurable security settings for organizations Connects to popular databases via JDBC, including MySQL, PostgreSQL, SQL Server, Oracle, Snowflake, SQLite, Cassandra, and BigQuery. Runs on Windows, macOS, and Linux. 7 million downloads, Pro users in 150 countries.

AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack. At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design. Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns. Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets. AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes. Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents structured access to metadata, lineage, dependencies and design rules. Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

ElectroNeek is an automation platform that combines AI agents, intelligent document processing, and RPA to automate business processes end to end. Teams build workflows in Studio Pro, a visual drag-and-drop editor with ready-made activities for web and desktop apps, Excel, email, PDFs, databases, and APIs, plus reusable subprograms to keep complex automations organized. IntelliDocs uses AI to extract and validate data from invoices, purchase orders, IDs, and other documents, then passes it directly into your workflows. AI agents add reasoning to bots so they can classify requests, make decisions, and handle exceptions that rule-based automation can't. Bot Runner executes automations attended or unattended on any machine, and Orchestrator lets you schedule, monitor, and manage bots and licenses from one web console. ElectroNeek serves enterprises, mid-market companies, and service partners who deliver automation to their own clients.

VisuaLeaf is a cross-platform database GUI for MongoDB, PostgreSQL, MySQL, SQL Server, and Oracle. It helps developers explore and edit data, build queries and MongoDB aggregation pipelines visually, create and reverse-engineer schema diagrams, manage indexes, analyze query performance, and work with an integrated MongoDB shell and SQL editor. VisuaLeaf also includes collection comparison, data synchronization, task automation, data masking, import and export tools, charts, dashboards, user management, and secure SSH and SOCKS5 connections. It is available for Windows, macOS, and Linux.

SkySQL is a multi-cloud, serverless database-as-a-service (DBaaS) platform designed to help businesses streamline their MySQL and MariaDB cloud database management with zero waste, instant auto-scaling capabilities, and 99.995% uptime. SkySQL offers serverless databases that save 80% of traditional database costs with pay-as-you-go pricing that scales according to demand, ensuring businesses only pay for what they use. With advanced features like SkyAI agents for building natural language interfaces to your database into your apps and providing AI-assisted performance optimization, businesses can easily handle complex workloads, minimize security risks, and accelerate AI application development. SkySQL offers both cost savings and high performance, on-demand scalability, and reliability, making it ideal for modern applications and growing businesses.

Observable is a data analysis and exploration platform that helps data analysts and their stakeholders understand their business data, build charts and other visualizations, and communicate insights. Built for teams, powered by AI, and backed by a global community of data practitioners, Observable offers a single workspace for data exploration, custom chart creation, and cross-functional data collaboration.

DbGate is a cross-platform SQL + NoSQL client that runs on Windows, macOS, Linux as desktop app, or in Docker - and then entirely in your browser. It has very powerful data browser, which allows you to quickly find or modify, what you need, even when using complicated relations. There are many filtering options allowing you in few clicks define quite complex conditions. You could of course use classical SQL editor with code completion or query designer. DbGate also has capability of design queries on NoSQL databases and event join results with SQL databases. Database compare tool is very fast, as it uses already cached DB models. You could browse and filter objects by type (table, view, procedure function) and by comparing status (equal, changed, added, removed). You could also deploy changes to database. Quite new feature is DbGate Cloud - online storage for connections and SQL scripts. You could also share folders with connections with others, with role-base permission access.

Union.ai is an award-winning, Flyte-based data and ML orchestrator for scalable, reproducible ML pipelines. With Union.ai, you can write your code locally and easily deploy pipelines to remote Kubernetes clusters. “Flyte’s scalability, data lineage, and caching capabilities enable us to train hundreds of models on petabytes of geospatial data, giving us an edge in our business.” — Arno, CTO at Blackshark.ai “With Flyte, we want to give the power back to biologists. We want to stand up something that they can play around with different parameters for their models because not every … parameter is fixed. We want to make sure we are giving them the power to run the analyses.” — Krishna Yeramsetty, Principal Data Scientist at Infinome “Flyte plays a vital role as a key component of Gojek's ML Platform by providing exactly that." — Pradithya Aria Pura, Principal Engineer at Goj

Connect to your data warehouse, and SSO authenticates your team in seconds. Organize your business intelligence as SQL. Make changes with confidence, automated testing validates every update. Deploy models confidently and travel back in time when things go wrong. Quary connects to your sensitive data store. In order to protect it, Quary is built from the ground up with security in mind. By default, data does not leave your estate, data exchanges happen between your Quary client and your data store. Transform data together, model, test, and deploy as a team. SSO is not an extra, we include it in our base plan and even help set it up. No one should share credentials. Quary builds upon your data store's access management systems and helps you manage it. We are in the process of implementing SOC2 and have security credentials (CISSP) on the team to ensure your data stays secure.

​Supaboard is an AI-powered business intelligence platform that enables users to analyze data and create real-time dashboards by simply asking questions in plain English. With one-click connections to over 60 data sources, including MySQL, PostgreSQL, Google Analytics, Shopify, Salesforce, and Notion, users can unify their data without a complex setup. It offers pre-trained, industry-specific AI analysts that generate SQL and NoSQL queries automatically, providing instant insights through charts, tables, and summaries. Users can build and embed customized dashboards by pinning responses and tailoring information for different audiences with filtered views. Supaboard ensures data security by connecting with read-only access, storing only schema metadata, and implementing granular access controls. Designed for universal usability, it minimizes operational overhead, allowing businesses to make data-driven decisions 10 times faster without requiring coding or data expertise.

SQLife is a modern, cross-platform database management tool for Oracle, PostgreSQL, MySQL, SQL Server, Redis, MongoDB, Kafka, RabbitMQ and more, built with JavaFX for DBAs and developers. ## Features * Connection properties with keep-alive, SSH tunnel and proxy * SQL editor with auto-completion, syntax highlighting and formatting * Data import/export (SQL, CSV, Excel, JSON, XML, Markdown, PNG) * SQL history with Git, Oracle Scheduler jobs, dark mode * MCP support, LLM Agent, schema comparison, locks monitor, 13 languages ## Latest Updates (2026-09-19) * AI model selector beside Send, searchable (provider/model) * Notifications when the AI finishes or needs input * SQL outline keeps comments and Markdown headings * Data grid column visibility menu with hidden columns * SFTP folder upload/download, side tabs, favorite paths * AI assistant sessions, MCP tools, logs, confirm forms * Fixes: Linux tray startup, password prompt, CSV/TSV paste, MCP cleanup

Dot (getdot.ai) is an AI data analyst. People ask in plain English in Slack, Microsoft Teams, the web app, or from AI agents through its MCP server and CLI. Dot finds the right tables, writes and runs SQL on the company's own warehouse, and answers with charts, data and the SQL it ran. Data teams train it with notes, dbt and semantic-layer context and evaluations, and a Context Agent keeps that knowledge current. It also builds data apps and scheduled reports. SOC 2 Type II and GDPR compliant.

Datus is an AI-assisted data engineering and analytics platform that builds a shared business context layer over an organization’s existing data stack. Its Datus Agent can inspect warehouse schemas, SQL, ETL code, and business documents to draft semantic models and connect business concepts, metrics, and source data. Teams review definitions and generated SQL, then use DOSI to validate compatible models and compile queries into native SQL for supported data sources. Datus provides a browser-based Studio, a local command-line agent, and REST, Python SDK, and MCP interfaces for analytics teams, data engineers, and AI agents. Common workflows include data discovery, semantic modeling, governed text-to-SQL, metric queries, SQL development, and production data engineering. It is designed to work with existing warehouses and model providers rather than require a data migration.

Dosi is a downloadable AI data analyst engine for data and software teams building AI agents and applications that answer questions about organizational data. It provides a semantic layer for defining business entities, metrics, relationships, and dimensions, then uses those definitions to translate natural-language questions into executable SQL. Teams can expose Dosi to compatible agents through the Model Context Protocol (MCP), or use its command-line interface and local server in developer workflows. Dosi connects to supported analytical databases and data warehouses, allowing queries to run against configured data sources while keeping business definitions consistent. Its intended uses include governed conversational analytics, agent-powered data exploration, and adding structured business context to AI-driven data applications.

The workflow automation platform for complex, mission-critical data and ML processes at scale. Flyte makes it easy to create concurrent, scalable, and maintainable workflows for machine learning and data processing. Flyte is used in production at Lyft, Spotify, Freenome, and others. At Lyft, Flyte has been serving production model training and data processing for over four years, becoming the de-facto platform for teams like pricing, locations, ETA, mapping, autonomous, and more. In fact, Flyte manages over 10,000 unique workflows at Lyft, totaling over 1,000,000 executions every month, 20 million tasks, and 40 million containers. Flyte has been battle-tested at Lyft, Spotify, Freenome, and others. It is entirely open-source with an Apache 2.0 license under the Linux Foundation with a cross-industry overseeing committee. Configuring machine learning and data workflows can get complex and error-prone with YAML.

LanceDB is a developer-friendly, open source database for AI. From hyperscalable vector search and advanced retrieval for RAG to streaming training data and interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application. Installs in seconds and fits seamlessly into your existing data and AI toolchain. An embedded database (think SQLite or DuckDB) with native object storage integration, LanceDB can be deployed anywhere and easily scales to zero when not in use. From rapid prototyping to hyper-scale production, LanceDB delivers blazing-fast performance for search, analytics, and training for multimodal AI data. Leading AI companies have indexed billions of vectors and petabytes of text, images, and videos, at a fraction of the cost of other vector databases. More than just embedding. Filter, select, and stream training data directly from object storage to keep GPU utilization high.

PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model. Graph databases are expensive, take months to set up, and need a dedicated team. Traditional graph databases can take hours to run multi-hop queries and struggle beyond 100GB of data. A separate graph database complicates your architecture with brittle ETLs and inflates your total cost of ownership (TCO). Connect to any data source anywhere. Cross-cloud and cross-region graph analytics. No complex ETLs or data replication is required. PuppyGraph enables you to query your data as a graph by directly connecting to your data warehouses and lakes. This eliminates the need to build and maintain time-consuming ETL pipelines needed with a traditional graph database setup. No more waiting for data and failed ETL processes. PuppyGraph eradicates graph scalability issues by separating computation and storage.

QStudio is a free, modern SQL editor supporting over 30 databases, including MySQL, PostgreSQL, and DuckDB. It offers features such as server browsing for easy viewing of tables, variables, functions, and configuration settings; SQL syntax highlighting; code completion; the ability to query servers directly from the editor; and built-in charts for data visualization. QStudio runs on Windows, Mac, and Linux, providing particularly good support for kdb+, Parquet, PRQL, and DuckDB. Additional functionalities include data pivoting similar to Excel, exporting data to Excel or CSV, and AI-powered tools like Text2SQL for generating queries from plain English, Explain-My-Query for code walkthroughs, and Explain-My-Error for debugging assistance. Simply send the query you want and select the chart type to draw a chart. Send queries straight from within the editor to any of your servers. All data structures are handled perfectly.

Streamkap is a streaming data platform that makes streaming as easy as batch. Stream data from database (change data capturee) or event sources to your favorite database, data warehouse or data lake. Streamkap can be deployed as a SaaS or in a bring your own cloud (BYOC) deployment.

Vanna.AI is an AI-powered platform designed to help users interact with their databases by asking questions in natural language. It enables both beginners and experts to quickly obtain insights from large datasets without needing to write complex SQL queries. Users simply ask a question, and Vanna automatically identifies the relevant tables and columns to retrieve the data needed. The platform integrates with popular databases like Snowflake, BigQuery, and Postgres and supports various front-end implementations such as Jupyter Notebooks, Slackbots, and web apps. Vanna's open source model allows for secure, self-hosted deployments and can continuously improve its performance as it learns from the user's interactions. It is ideal for businesses looking to democratize access to data insights and simplify the query process.

​Tad is a free (MIT Licensed) desktop application for viewing and analyzing tabular data. It is a fast viewer for CSV and Parquet files and SQLite and DuckDb databases that support large files. It's a Pivot Table for analyzing and exploring data. Internally, Tad uses DuckDb for fast, accurate processing. Designed to fit into the workflow of data engineers and data scientists. Tad includes updates to DuckDb 1.0, the ability to export filtered tables as Parquet (as well as CSV), a fix for formatting numbers in scientific notation, and other minor bug fixes and dependent package upgrades. A packaged installer for Tad is available for macOS (x86 and Apple Silicon), Linux, and Windows.

nao is an AI-powered data IDE designed specifically for data teams, combining a code editor with native integration to your data warehouse so you can write, test, and maintain data-centric code with full context. It supports warehouses such as Postgres, Snowflake, BigQuery, Databricks, DuckDB, Motherduck, Athena, and Redshift. Once connected, nao replaces a traditional data-warehouse console by offering schema-aware SQL auto-completion, data previews, SQL worksheets, and the ability to switch easily between multiple warehouses. The core of nao is its AI agent, which has full awareness of your actual data schema, tables, columns, metadata, and your codebase or data-stack context. It can generate SQL queries or full data-transformation models (e.g., for dbt workflows), refactor code, add or update documentation, run data-quality checks and data-diff tests, and even surface insights or run exploratory analytics, all while respecting data structure and quality constraints.

SQL is a domain-specific programming language used for accessing, managing, and manipulating relational databases and relational database management systems.

Enrich.sh is a high-performance data enrichment infrastructure platform as a service designed to power real-time data workflows at scale with minimal latency and high throughput. It enables businesses and developers to enrich, process, and transform large volumes of data (500+ requests per second) with sub-millisecond response times, making it suitable for performance-sensitive and edge-oriented applications. It is built for big data at the edge, offering a backend service that handles enrichment workloads efficiently without the need for heavy operational overhead, allowing teams to focus on core product development rather than infrastructure management. Enrich.sh provides robust APIs that let users ingest, augment, and serve enriched data quickly, supporting complex enrichment strategies and rapid data pipelines for analytical or transactional use cases.

We’re MotherDuck, a software company founded by a passionate flock of experienced data geeks. We’ve worked as leaders for some of the greatest companies in data. Scale-out is expensive and slow, let’s scale up. Big Data is dead, long live easy data. Your laptop is faster than your data warehouse. Why wait for the cloud? DuckDB slaps, so let’s supercharge it. When we founded MotherDuck we recognized that DuckDB might just be the next major game changer thanks to its ease of use, portability, lightning-fast performance, and rapid pace of community-driven innovation. At MotherDuck, we want to help the community, the DuckDB Foundation, and DuckDB Labs build greater awareness and adoption of DuckDB, whether users are working locally or want a serverless always-on way to execute their SQL. We are a world-class team of engineers and leaders with experience working on databases and cloud services at AWS, Databricks, Elastic, Facebook, Firebolt, Google BigQuery, Neo4j, SingleStore, and more.

Kestra is an open-source, event-driven orchestrator that simplifies data operations and improves collaboration between engineers and business users. By bringing Infrastructure as Code best practices to data pipelines, Kestra allows you to build reliable workflows and manage them with confidence. Thanks to the declarative YAML interface for defining orchestration logic, everyone who benefits from analytics can participate in the data pipeline creation process. The UI automatically adjusts the YAML definition any time you make changes to a workflow from the UI or via an API call. Therefore, the orchestration logic is defined declaratively in code, even if some workflow components are modified in other ways.

Databricks Unity Catalog is the industry’s only unified and open governance solution for data and AI, built into the Databricks Data Intelligence Platform. With Unity Catalog, organizations can seamlessly govern both structured and unstructured data in any format, as well as machine learning models, notebooks, dashboards, and files across any cloud or platform. Data scientists, analysts, and engineers can securely discover, access, and collaborate on trusted data and AI assets across platforms, leveraging AI to boost productivity and unlock the full potential of the lakehouse environment. This unified and open approach to governance promotes interoperability and accelerates data and AI initiatives while simplifying regulatory compliance. Easily discover and classify both structured and unstructured data in any format, including machine learning models, notebooks, dashboards, and files across all cloud platforms.