TimeSeries.Guru Alternatives
TimeSeries.Guru is described as 'A relaxing hosted time series database. TSDB with sophisticated querying, joining and aggregation via HTTP REST API. Storage from 1 GB to Terabytes. On-Demand and Pay-Per-Use. Cloud ready' and is an website. There are six alternatives to TimeSeries.Guru, not only websites but also apps for a variety of platforms, including Linux, BSD, Self-Hosted solutions, Python and fontconfig. The best alternative is Graphite Monitoring, which is both free and Open Source. Other great sites and apps similar to TimeSeries.Guru are KairosDB, OpenTSDB, Axibase Time Series Database and Cube.
Graphite is a highly scalable real-time graphing system. As a user, you write an application that collects numeric time-series data that you are interested in graphing, and send it to Graphite's processing backend, carbon, which stores the data in Graphite's specialized...
KairosDB is a fast distributed scalable time series database written on top of Cassandra.
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...
Features
ATSD is purpose-built for analyzing and reporting on massive volumes of time-series data collected at high frequency. Features include data analytics, visualization, data forecasting, reporting, alerting. All in one product built for big data.
Cube is a system for collecting timestamped events and deriving metrics. By collecting events rather than metrics, Cube lets you compute aggregate statistics post hoc. It also enables richer analysis, such as quantiles and histograms of arbitrary event sets.
Features
DiscontinuedLast release in 2013, GitHub project archived.
DalmatinerDB is a metric database written in Erlang. It takes advantage of special properties of metrics to make trade-offs. The goal is to make a store for metric data (time, values) that is fast, has a low overhead, and is easy to query and manage.
Features