InfluxDB is an open source time series platform. This includes APIs for storing and querying data, processing it in the background for ETL or monitoring and alerting purposes, user dashboards, and visualizing and exploring the data and more. The master branch on this repo now represents the latest InfluxDB, which now includes functionality for Kapacitor (background processing) and Chronograf (the UI) all in a single binary.  It is designed to handle high write and query loads and provides a SQL-like query language called InfluxQL for interacting with data.

InfluxDB - Scalable datastore for metrics, events, and real-time analytics

OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase.  OpenTSDB was written to address a common need: store, index and serve metrics collected from computer systems (network gear, operating
systems, applications) at a large scale, and make this data easily accessible and graphable.

OpenTSDB - A scalable, distributed Time Series Database.

TDengine is an open-source big data platform designed and optimized for Internet of Things (IoT), Connected Vehicles, and Industrial IoT. Besides the 10x faster time-series database, it provides caching, stream computing, message queuing and other functionalities to reduce the complexity and costs of development and operations.
 
<ul><li>10x Faster on Insert/Query Speeds: Through the innovative design on storage, on a single-core machine, over 20K requests can be processed, millions of data points can be ingested, and over 10 million data points can be retrieved in a second. It is 10 times faster than other databases.</li><li>1/5 Hardware/Cloud Service Costs: Compared with typical big data solutions, less than 1/5 of computing resources are required. Via column-based storage and tuned compression algorithms for different data types, less than 1/10 of storage space is needed.</li><li>Full Stack for Time-Series Data: By integrating a database with message queuing, caching, and stream computing features together, it is no longer necessary to integrate Kafka/Redis/HBase/Spark or other software. It makes the system architecture much simpler and more robust.</li><li>Powerful Data Analysis: Whether it is 10 years or one minute ago, data can be queried just by specifying the time range. Data can be aggregated over time, multiple time streams or both. Ad Hoc queries or analyses can be executed via TDengine shell, Python, R or Matlab.</li><li>Seamless Integration with Other Tools: Telegraf, Grafana, Matlab, R, and other tools can be integrated with TDengine without a line of code. MQTT, OPC, Hadoop, Spark, and many others will be integrated soon.</li><li>Zero Management, No Learning Curve: It takes only seconds to download, install, and run it successfully; there are no other dependencies. Automatic partitioning on tables or DBs. Standard SQL is used, with C/C++, Python, JDBC, Go and RESTful connectors.</li></ul><div> </div>

TDengine is an open-source big data platform designed and optimized for Internet of Things (IoT), Connected Vehicles, and Industrial IoT. Besides the 10x faster time-series database, it provides caching, stream computing, message queuing and other functionalities to reduce the complexity and costs of development and operations.

TDengine -  Big data platform designed and optimized for the Internet of Things

Graphite is an enterprise-scale monitoring tool that runs well on cheap hardware. It is a highly scalable real-time graphing system. It stores numeric time-series data and renders graphs of this data on demand. 

Graphite - A highly scalable real-time graphing system

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Prometheus - Service Monitoring System and Time Series Database

LinDB is an open-source Time Series Database which provides high performance, high availability and horizontal scalability. LinDB takes a lot of best practice of TSDB and implements some optimizations based on the characteristics of time series data. Unlike writing a lot of Continuous-Query for InfluxDB, LinDB supports rollup in specific interval automatically after creating the database. Moreover, LinDB is extremely fast for parallel querying and computing of distributed time series data.
 
LinDB supports Metric + Tags + Fields, and is schema-free; The LinQL is handy for realtime data analytics. Tags based sharding strategy in LinDB solves the hotspots problem, and is truly horizontally expanded available by simply adding new broker and storage nodes.

LinDB is an open-source Time Series Database which provides high performance, high availability and horizontal scalability. LinDB takes a lot of best practice of TSDB and implements some optimizations based on the characteristics of time series data. Unlike writing a lot of Continuous-Query for InfluxDB, LinDB supports rollup in specific interval automatically after creating the database. Moreover, LinDB is extremely fast for parallel querying and computing of distributed time series data.


Lindb - Distributed Time Series Database

InfluxDB is an open-source, distributed, time series database with no external dependencies. It's useful for recording metrics, events, and performing analytics. Everything in InfluxDB is a time series that you can perform standard functions on like min, max, sum, count, mean, median, percentiles, and more. Collect your data on any interval and compute rollups on the fly later.

InfluxDB - Distributed Time Series Database

Hawkular Metrics is a metrics collection, aggregation, visualization framework. Hawkular is a set of Open Source projects designed to be a generic solution for common monitoring problems. The Hawkular projects provide REST services that can be used for all kinds of monitoring needs. The aim is to provide a generic solution that can be used for common monitoring problems.
 
The main goal of the Hawkular organization is to provide tools to monitor, view, predict, and guide you to make informed decisions about deployed applications and infrastructure. Anyone looking for Java-based components for alerting, metric storage, or distributed tracing should be interested in Hawkular.

Hawkular Metrics is a metrics collection, aggregation, visualization framework. Hawkular is a set of Open Source projects designed to be a generic solution for common monitoring problems. The Hawkular projects provide REST services that can be used for all kinds of monitoring needs. The aim is to provide a generic solution that can be used for common monitoring problems.


Hawkular metrics - Time Series Metrics Engine based on Cassandra

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InfluxDB - Scalable datastore for metrics, events, and real-time analytics

OpenTSDB - A scalable, distributed Time Series Database.

TDengine - Big data platform designed and optimized for the Internet of Things

Graphite - A highly scalable real-time graphing system

Prometheus - Service Monitoring System and Time Series Database

Lindb - Distributed Time Series Database

InfluxDB - Distributed Time Series Database

Hawkular metrics - Time Series Metrics Engine based on Cassandra

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