时序数据库全称为时间序列数据库。时间序列数据库主要用于指处理带时间标签（按照时间的顺序变化，即时间序列化）的数据，带时间标签的数据也称为时间序列数据。时序数据的兴起还是榜上了物联网的大风。物联网（Internet of Things，简称IOT）是指通过各种信息传感器实时采集任何需要管理设备的信息，并进行管理。物联网的基础数据具有数据量大、结构单一、时间属性强、查询简单等特点，传统的关系型数据库在面对物联网数据时，显得应对发力，基本上属于功能过剩但性能不足。
DBMS for storing time series, events and metrics
InfluxDB empowers developers to build IoT, analytics and monitoring software. It is purpose-built to handle the massive volumes and countless sources of time-stamped data produced by sensors, applications and infrastructure.
High performance Time Series DBMS
Open-source TimeSeries DBMS and monitoring system
Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. Since its inception in 2012, many companies and organizations have adopted Prometheus, and the project has a very active developer and user community. It is now a standalone open source project and maintained independently of any company. To emphasize this, and to clarify the project’s governance structure, Prometheus joined the Cloud Native Computing Foundation in 2016 as the second hosted project, after Kubernetes.
Data logging and graphing tool for time series data
Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.
RRDtool is the OpenSource industry standard, high performance data logging and graphing system for time series data. RRDtool can be easily integrated in shell scripts, perl, python, ruby, lua or tcl applications.
A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data
Fauna (previously named FaunaDB) provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.
Scalable Time Series DBMS based on HBase
Scalable in-memory time series database optimized for IoT and Big Data
GridDB is an innovative solution to solve these complex problems. The foundation of GridDB’s principles is based upon offering a versatile data store that is optimized for IoT, provides high scalability, is tuned for high performance, and ensures high reliability.
Time Series DBMS for big data, integrated with a lightweight distributed computing framework and a vector programming language
DolphinDB is a high performance time-series database. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. DolphinDB offers operational simplicity, scalability, fault tolerance, and concurrency.
Distributed Time Series DBMS based on Cassandra or H2
One of the modules of TDengine is the time-series database. However, in addition to this, to reduce the complexity of research and development and the difficulty of system operation, TDengine also provides functions such as caching, message queuing, subscription, stream computing, etc. TDengine provides a full-stack technical solution for the processing of IoT and Industrial Internet BigData. It is an efficient and easy-to-use IoT Big Data platform.
TDengine uses standard SQL language to provide main functions and follow standardization specifications.
版权声明：本文内容由互联网用户自发贡献，该文观点仅代表作者本人。本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容， 请发送邮件至 举报，一经查实，本站将立刻删除。