#database-technology

#database-technology

SkySQL has raised $6.6 million to integrate conversational AI into databases.

ScyllaDB is crucial for managing the data demands of today's AI-driven world.

MongoDB claims to be gaining market share against PostgreSQL by addressing limitations in scalability and flexibility for applications like Fanatics Betting & Gaming.

PostgreSQL is increasingly favored among developers for AI-related applications due to its flexibility, reliability, and robust extensibility.

An open source project aims to enhance PostgreSQL's analytics capabilities by integrating the DuckDB analytics engine.

Relational databases may not be suitable for all applications; assess your needs.

Signs of outgrowing relational databases include complex schemas and performance issues.

The Amazon Aurora PostgreSQL Limitless Database enables automated scaling of relational database workloads, enhancing performance for massive data and transaction management.

NoSQL databases are evolving to meet modern application requirements that demand massive scalability and high performance.

Redis has improved its database's innovation through a dual licensing strategy, promising enhanced features and cost reductions for developers.

Amazon Aurora DSQL offers a new level of performance and scalability for SQL databases, focusing on high availability and strong consistency.

Azure SQL Database now supports native vector functionality, streamlining complex data processing for AI applications.

Tencent has developed X-Stor, a NoSQL database designed to support multiple data models simultaneously, optimizing resource utilization and reducing redundancy.