Best of NoSQL — July 2024

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   Article

   Substack·2y

   A Primer on Databases

   Databases have been fundamental to software development for decades. The post discusses their history, from the invention of SQL databases to the rise of unstructured and cloud-based databases. It highlights the current database landscape, including the significance of transaction processing and analytics. The piece also touches on emerging technologies like vector databases, which are crucial for AI development. The author emphasizes that while the core technology of databases is not extremely complex, distribution and platformization will be key factors for future success in the database market.

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2. 2
   Article

   swizec.com·2y

   Why SQL is Forever

   SQL and relational databases remain fundamental for transactional data, despite the advances and popularity of NoSQL technologies over the past decades. Many NoSQL systems have either been removed, adapted to include SQL/natively support transactions, or are mainly used for caching and analytics. This demonstrates the enduring flexibility and utility of SQL, including new features like JSON support and vector databases, which relational databases have successfully integrated while maintaining ACID properties.

   121

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3. 3
   Article

   Dev Squad·2y

   MongoDB Essentials: What is MongoDB, Collections, and Documents?

   MongoDB is a NoSQL database that uses a flexible, document-oriented approach to store data instead of the traditional table-based structure. A collection in MongoDB groups together multiple documents and acts like a folder in a file system. Documents, the basic unit of data in MongoDB, are similar to records in a spreadsheet or JSON objects, containing various fields and values representing the data.

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4. 4
   Article

   P99 Conf·2y

   NoSQL, NoMQ: Palo Alto Networks’ New Event Streaming Paradigm

   Palo Alto Networks processes terabytes of network security events daily, requiring a system that can efficiently correlate and analyze millions of events per second. To reduce operational costs and complexity, they opted to eliminate the traditional message queue (Kafka) and use their existing low-latency NoSQL database (ScyllaDB) for real-time event correlation. This approach allowed them to enhance performance and lower operational overhead while maintaining high throughput and robust data correlation capabilities.

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