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DuckDB

DuckDB is an in-process SQL OLAP database management system.

DuckDB

DuckDB Reviews and Details

This page is designed to help you find out whether DuckDB is good and if it is the right choice for you.

Screenshots and images

  • DuckDB Landing page
    Landing page //
    2023-06-18

Features & Specs

  1. Lightweight

    DuckDB is a lightweight database that is easy to install and use without requiring a separate server process.

  2. In-Memory Processing

    It supports efficient in-memory execution, which makes it suitable for analytical queries that require quick data processing.

  3. Columnar Storage

    DuckDB uses a columnar storage format that optimizes for analytical workloads by improving read performance for large datasets.

  4. Integration with Data Science Tools

    The database integrates well with popular data science tools and libraries such as Pandas, R, and Jupyter Notebooks.

  5. SQL Support

    DuckDB offers full support for SQL, allowing users to leverage their existing SQL knowledge without having to learn new query languages.

  6. Open Source

    DuckDB is open-source, enabling users to inspect the code, contribute to its development, and use it without licensing costs.

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Videos

DuckDB An Embeddable Analytical Database

DuckDB: Hi-performance SQL queries on pandas dataframe (Python)

DuckDB An Embeddable Analytical Database

Social recommendations and mentions

We have tracked the following product recommendations or mentions on various public social media platforms and blogs. They can help you see what people think about DuckDB and what they use it for.
  • pdo_duckdb: DuckDB for PHP, Behind the PDO API You Already Know
    DuckDB is the closest thing the analytics world has to SQLite. It runs in-process, needs no server, reads and writes a single file, and chews through columnar aggregate queries that would make a row-store sweat. PHP has shipped PDO_SQLite in core for twenty years. Until now it had no equivalent for DuckDB. - Source: dev.to / about 1 month ago
  • From DeepSeek to Quack: When the Dream of Distributed DuckDB Started to Feel Real
    DeepSeek released Smallpond, a lightweight data processing framework built on DuckDB and 3FS. The idea was surprisingly simple: instead of building everything around a traditional big-data engine like Spark, run many independent DuckDB-based processing jobs close to the data, partition the workload carefully, and let each local engine do what it does best. - Source: dev.to / 2 months ago
  • Your MCP server is not an API adapter
    The server embeds DuckDB in-process and loads pre-aggregated views and lookup Tables at startup. Some are straight copies of small reference tables. Others Are materialized summaries that flatten joins the source database was never Designed to run efficiently, the kind of cross-table aggregations that make Sense for an analytical question but would be expensive on a schema built for Transactional web UI... - Source: dev.to / 3 months ago
  • I Scraped 47M+ Hacker News Items Into Parquet Files โ€“ Here's What I Discovered About HN's Hidden Data Patterns
    I recommend using DuckDB for querying large Parquet files โ€“ it's incredibly fast and handles the heavy lifting without requiring you to load everything into memory at once. - Source: dev.to / 4 months ago
  • How to Analyze Sensitive Data Without Uploading It Anywhere
    DuckDB is an embeddable SQL database built for analytics. It's fast, handles CSVs natively, and โ€” crucially โ€” it compiles to WebAssembly, which means it runs entirely inside your browser tab. - Source: dev.to / 5 months ago
  • I Built a Self-Hosted Google Trends Alternative with DuckDB
    I use DuckDB for this. For this workload (rank comparisons, volatility calculations, detecting new entrants), DuckDBโ€™s SQL engine is ideal. - Source: dev.to / 5 months ago
  • Distributed SQL engine for ultra-wide tables
    Check the Vortex file format (https://vortex.dev/), if you are interested in a distributed SQL engine then you can check SpiralDB (https://spiraldb.com/), I havenโ€™t used this one personally but they created Vortex. If you can drop the โ€œdistributedโ€ part, then plug DuckDB (https://duckdb.org/) and query Parquet (out of the box) or Vortex (https://duckdb.org/docs/stable/core_extensions/vortex.html) with it. - Source: Hacker News / 6 months ago
  • Tech Stack Lessons from scaling 20x in a year
    The results surprised us. P99 latency actually improved. Why? Most queries are "give me the last 5 minutes of metrics" or "show me the last 500 logs." That's all hot data sitting in Postgres. Historical queries hit S3, and DuckDB handles Parquet files like a champ. Those are, if not cached, of course slightly slower. - Source: dev.to / 6 months ago
  • Getting Started Building a Data Platform
    Shaper is a simple interface on top of DuckDB that allows you to build analytics dashboards and automate data workflows with only SQL. - Source: dev.to / 9 months ago
  • From OLTP to OLAP: Streaming Databases into MotherDuck with Estuary
    DuckDB is an open source analytical database designed with a clear goal: to make complex queries fast and simple without heavy infrastructure. Instead of being a traditional client-server database, DuckDB is embedded. It runs inside the host process, which reduces overhead and makes it easy to integrate directly into applications, notebooks, or scripts. Several features stand out:. - Source: dev.to / 10 months ago
  • DuckDB + Iceberg: The ultimate synergy
    Apache Iceberg and DuckDB have established themselves as key players in data architecture landscape. With DuckDB 1.4's native support for Iceberg writes, combined with Apache Polaris and MinIO, this promising stack offers efficiency, scalability, and flexibility. - Source: dev.to / 10 months ago
  • DuckDB on AWS Lambda: The Easy Way with Layers
    It seemed like the perfect opportunity to explore DuckDB, an in-process analytical database known for its efficiency and simplicity. - Source: dev.to / 10 months ago
  • From Go to Rust: Supercharging Our ClickHouse UDFs with Alloy
    While our Go-based implementation has served us well, we've been exploring whether Rustโ€”with its rapidly maturing Ethereum ecosystemโ€”could take us even further. The potential benefits are compelling: better performance, enhanced safety, and improved portability that could make it easier to bring these UDFs to other analytical engines like DataFusion or DuckDB. - Source: dev.to / about 1 year ago
  • Show HN: TextQuery โ€“ Query CSV, JSON, XLSX Files with SQL
    Have you seen duckdb? https://duckdb.org/ It's basically what you're building, but more low-level. Really cool, to be honest -- serves the same market too. Do you have any significant differentiator, other than charts? - Source: Hacker News / about 1 year ago
  • Why You Shouldnโ€™t Invest In Vector Databases?
    In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / about 1 year ago
  • Every Database Will Support Iceberg โ€” Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration โ€” Spark, Flink, Trino, DuckDB, Snowflake, RisingWave โ€” can read and/or write Iceberg data directly. - Source: dev.to / about 1 year ago
  • How to Pitch Your Boss to Adopt Apache Iceberg?
    Want to use Snowflake today and switch to Trino tomorrow? Prefer to experiment with a free tool like DuckDB for smaller tasks? Iceberg supports it all. - Source: dev.to / over 1 year ago
  • ๐Ÿ”ฌPublic docker images Trivy scans as duckdb datas on Kaggle
    Deliver nice ready-to-use data as duckdb, parquet and csv. - Source: dev.to / over 1 year ago
  • How I Built My Own Last.fm Clone on Blueskyโ€™s AT Protocol โ€” Join the Beta!
    Analytics: DuckDB โ€“ Efficient in-memory analytics for trends and insights. - Source: dev.to / over 1 year ago
  • Building on modern web app architecture
    I called the WASM/WebGL-enabled future a โ€œquiet revolutionโ€ because itโ€™s been bizarrely under-discussed. Web developers know about it, but people responsible for strategic thinking around software and computing products are only now beginning to see the possibilities. Projects that have taken advantage of them are transforming and disrupting their industries, with standouts like duck-db (an in memory SQL database)... - Source: dev.to / over 1 year ago
  • Outgrowing Postgres: Handling increased user concurrency
    Specialized databases: For analytical workloads, consider using a dedicated analytical database optimized for high-concurrency, low-latency queries on large datasets like Pinot, DuckDB, or ahem Tinybird. - Source: dev.to / over 1 year ago

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Is DuckDB good? This is an informative page that will help you find out. Moreover, you can review and discuss DuckDB here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.