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Based on our record, Apache Parquet should be more popular than ArangoDB. It has been mentiond 25 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you like the document db idea there are a lot of choices, especially https://arangodb.com/ which I think gets little attention because people who use it see it as a secret weapon. Too bad about the license though. Also https://couchdb.apache.org/ and https://developer.marklogic.com/. - Source: Hacker News / about 1 year ago
ArangoDB is a multi-model database that supports document, key-value, and graph data models with a unified query language. - Source: dev.to / over 1 year ago
In modern databases, efficient data serialization and deserialization are paramount to achieving high performance. ArangoDB, a multi-model database, addresses this need with its innovative binary data format, VelocyPack. This article delves into the intricacies of VelocyPack, demonstrating its advantages, usage, and how it enhances the performance of ArangoDB with code examples in Java and Rust. - Source: dev.to / over 1 year ago
ArangoDB: A native multi-model database, it offers flexibility for documents, graphs, and key-values. This versatility makes it suitable for applications requiring a combination of these data models. - Source: dev.to / over 1 year ago
ArangoDB, a "multi-modal" database engine that stores arbitrary JSON documents like MongoDB, key/value data like Redis, and graph relationships like Neo4j โ and lets you leverage all three kinds of data in a single query. Source: almost 3 years ago
If there was a way to package and compress the Excel spreadsheet in a web-friendly format, then there's nothing stopping us from loading the entire dataset in the browser!1 Sure enough, the Parquet file format was specifically designed for efficient portability. - Source: dev.to / about 1 month ago
Iceberg decouples storage from compute. That means your data isnโt trapped inside one proprietary system. Instead, it lives in open file formats (like Apache Parquet) and is managed by an open, vendor-neutral metadata layer (Apache Iceberg). - Source: dev.to / 6 months ago
Data prep kit github repository: https://github.com/data-prep-kit/data-prep-kit?tab=readme-ov-file Quick start guide: https://github.com/data-prep-kit/data-prep-kit/blob/dev/doc/quick-start/contribute-your-own-transform.md Provided samples and examples: https://github.com/data-prep-kit/data-prep-kit/tree/dev/examples Parquet: https://parquet.apache.org/. - Source: dev.to / 6 months ago
Deliver nice ready-to-use data as duckdb, parquet and csv. - Source: dev.to / 6 months ago
Push the dataset to hugging face in parquet format. - Source: dev.to / 11 months ago
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
DuckDB - DuckDB is an in-process SQL OLAP database management system