DuckDB
Processing and storing tabular datasets, e.g. from CSV or Parquet files. Large result set transfer to client. Large client/server installations for centralized enterprise data warehousing. Writing to a single database from multiple concurrent processes. DuckDB is a relational database management system (RDBMS). That means it is a system for managing data stored in relations. A relation is essentially a mathematical term for a table. Each table is a named collection of rows. Each row of a given table has the same set of named columns, and each column is of a specific data type. Tables themselves are stored inside schemas, and a collection of schemas constitutes the entire database that you can access.
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Duck Creek Claims
Duck Creek Claims is a comprehensive claims management solution designed to streamline the entire claims lifecycle for insurers. From the initial report to final settlement, it automates workflows, simplifies data analysis through integrated analytics, and ensures seamless integration with existing systems. Key features include dynamic first notice of loss (FNOL) capabilities, automated assignment based on adjuster skills and workload, instant access to policy and coverage data, and efficient adjuster workflows. By enhancing operational efficiency and reducing manual workloads, Duck Creek Claims enables faster claims resolution, improved customer satisfaction, and compliance with the latest regulations.
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nao
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.
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Tad
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.
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