RedisTimeSeries is an open source time series data database built on the basis of Redis memory database. It provides efficient time series data storage and query functions, suitable for storing and processing large-scale time series data. RedisTimeSeries supports multiple query languages and Redis API, which can be easily integrated with other applications.
Here are some key features of RedisTimeSeries:
- Efficient memory storage: RedisTimeSeries uses the Redis memory database as the storage medium, which can provide high-speed read and write performance. It also supports persistent storage, which saves data to disk to prevent data loss.
- Multiple data types support: RedisTimeSeries supports multiple time series data types, including floating point numbers, integers, Boolean values, strings, etc. It also supports multidimensional data, which can combine multiple time series data into one data set for storage and query.
- Multiple query language support: RedisTimeSeries supports multiple query languages, including Redis commands, SQL query language and REST API. This enables users to choose an appropriate query method for data query and analysis according to their needs.
- Scalability and high availability: RedisTimeSeries supports distributed deployment and can be easily extended to multiple nodes and multiple data centers. It also supports master-slave replication and cluster deployment, which can provide high availability and disaster recovery and fault tolerance.
In short, RedisTimeSeries is a powerful time series data database, suitable for storing and processing large-scale time series data. It provides efficient data storage and query functions, supports multiple query languages and Redis API, and can be easily integrated with other applications. RedisTimeSeries is also scalable and highly available, and can be easily extended to multiple nodes and multiple data centers.
An open source system that can combine time series database and vector database
There is currently no complete open source system that can integrate time series databases and vector databases together.
However, you can refer to the following open source projects to build a combined solution yourself