Both SurrealDB and InfluxDB are prominent open-source projects, each with a substantial following and distinct use cases. SurrealDB, with 31,669 stars, has seen a notable increase in popularity, gaining 312 stars in the last 30 days. This momentum suggests a growing interest in its capabilities as a scalable, distributed, collaborative, document-graph database designed for real-time web applications. Its star count indicates a robust community, which is likely attracted to its unique blend of document and graph data models, making it suitable for applications requiring complex relationships and real-time data processing. InfluxDB, on the other hand, has accumulated 31,344 stars and has gained 164 stars in the last 30 days. While its recent momentum is slightly lower than SurrealDB's, it remains a highly regarded project. InfluxDB is optimized for time-series data, making it an ideal choice for metrics, events, and real-time analytics. Its community is well-established, reflecting its long-standing reputation in the field of time-series databases. This makes InfluxDB a go-to solution for monitoring, IoT, and other applications where time-stamped data is crucial. Both projects have significant community support and are tailored for different but equally important use cases in the realm of real-time data management. SurrealDB's recent surge in popularity highlights its potential for applications needing a flexible, real-time database, while InfluxDB's steady following underscores its reliability and effectiveness in handling time-series data.