Lightweight
DuckDB is a lightweight database that is easy to install and use without requiring a separate server process.
In-Memory Processing
It supports efficient in-memory execution, which makes it suitable for analytical queries that require quick data processing.
Columnar Storage
DuckDB uses a columnar storage format that optimizes for analytical workloads by improving read performance for large datasets.
Integration with Data Science Tools
The database integrates well with popular data science tools and libraries such as Pandas, R, and Jupyter Notebooks.
SQL Support
DuckDB offers full support for SQL, allowing users to leverage their existing SQL knowledge without having to learn new query languages.
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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Check the traffic stats of DuckDB on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
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The latest comments about DuckDB on Reddit. This can help you find out how popualr the product is and what people think about it.
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
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
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 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
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 use DuckDB for this. For this workload (rank comparisons, volatility calculations, detecting new entrants), DuckDBโs SQL engine is ideal. - Source: dev.to / 5 months ago
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 havenโt used this one personally but they created Vortex. If you can drop the โdistributedโ 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
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
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
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
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
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
While our Go-based implementation has served us well, we've been exploring whether Rustโwith its rapidly maturing Ethereum ecosystemโcould 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
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
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
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
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
Deliver nice ready-to-use data as duckdb, parquet and csv. - Source: dev.to / over 1 year ago
Analytics: DuckDB โ Efficient in-memory analytics for trends and insights. - Source: dev.to / over 1 year ago
I called the WASM/WebGL-enabled future a โquiet revolutionโ because itโs 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
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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