Displaying 1 to 20 from 27 results

Timescaledb - An open-source time-series database optimized for fast ingest and complex queries

  •    PLpgSQL

TimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL, providing automatic partitioning across time and space (partitioning key), as well as full SQL support. TimescaleDB is packaged as a PostgreSQL extension and released under the Apache 2 open-source license.

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

  •    Go

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.

OpenTSDB - A scalable, distributed Time Series Database.

  •    Java

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.

Druid IO - Real Time Exploratory Analytics on Large Datasets

  •    Java

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations. Druid can load both streaming and batch data.




Graphite - A highly scalable real-time graphing system

  •    Python

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.

Prometheus - Service Monitoring System and Time Series Database

  •    Go

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.

Kairosdb - Fast distributed scalable time series database written on top of Cassandra

  •    Java

KairosDB is a fast distributed scalable time series database written on top of Cassandra. Data can be pushed in KairosDB via multiple protocols : Telnet, Rest, Graphite. KairosDB stores time series in Cassandra, the popular and performant NoSQL datastore. It supports aggregators which can perform an operation on data points and down samples. Standard functions like min, max, sum, count, mean etc.

Blueflood - A distributed system designed to ingest and process time series data

  •    Java

Blueflood is a high throughput, low latency, multi-tenant distributed metric processing system behind Rackspace Metrics, which is currently used in production by the Rackspace Monitoring team and Rackspace Public Cloud team to store metrics generated by their systems. Data from Blueflood can be used to construct dashboards, generate reports, graphs or for any other use involving time-series data. It focuses on near-realtime data, with data that is queryable mere milliseconds after ingestion.


Atlas - In-memory dimensional time series database

  •    Scala

Atlas was developed by Netflix to manage dimensional time series data for near real-time operational insight. Atlas features in-memory data storage, allowing it to gather and report very large numbers of metrics, very quickly. Atlas captures operational intelligence. Whereas business intelligence is data gathered for analyzing trends over time, operational intelligence provides a picture of what is currently happening within a system.

QuestDB - Fast relational time-series database

  •    Java

QuestDB is an open-source NewSQL relational database designed to process time-series data, faster. QuestDB ingests data via HTTP, PostgresSQL wire protocol, Influx line protocol or directly from Java. Reading data is done using SQL via HTTP, PostgreSQL wire protocol or via Java API. The whole database and console fits in a 3.5Mb package.

Lindb - Distributed Time Series Database

  •    Go

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.

InfluxDB - Distributed Time Series Database

  •    Go

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.

TrailDB - Efficient tool for storing and querying series of events

  •    C

TrailDB is a library, implemented in C, which allows you to query series of events at blazing speed. TrailDB is also optimized for speed of development: Use its simple API with your favorite language, in your favorite environment. TrailDB's secret sauce is data compression. It leverages predictability of time-based data to compress your data to a fraction of its original size. In contrast to traditional compression, you can query the encoded data directly, decompressing only the parts you need.

Hawkular metrics - Time Series Metrics Engine based on Cassandra

  •    Java

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.

Beringei - High performance, in-memory storage engine for time series data.

  •    C++

In the fall of 2015, we published the paper “Gorilla: A Fast, Scalable, In-Memory Time Series Database” at VLDB 2015. Beringei is the open source representation of the ideas presented in this paper. Beringei is a high performance time series storage engine. Time series are commonly used as a representation of statistics, gauges, and counters for monitoring performance and health of a system.

Timely - Accumulo backed time series database

  •    Java

Timely is a time series database application that provides secure access to time series data. Timely is written in Java and designed to work with Apache Accumulo and Grafana.

DalmatinerDB - Fast distributed metrics database in Erlang

  •    Erlang

DalmatinerDB is a metric database written in pure Erlang. It takes advantage of some special properties of metrics to make some tradeoffs. Its goal is to make a store for metric data (time, value of a metric) that is fast, has a low overhead, and is easy to query and manage. DalmatinerDB allows for metric input in second or even sub-second precision. It will interpolate the missing values to the best of it’s abilities. This is usually acceptable for aggregated data.

Akumuli - Time-series database

  •    C++

Akumuli is a time-series database for modern hardware. It can be used to capture, store and process time-series data in real-time. The word "akumuli" can be translated from Esperanto as "accumulate".

SiriDB - Highly-scalable, robust and super fast time series database

  •    C

SiriDB is a highly-scalable, robust and super fast time series database. Build from the ground up SiriDB uses a unique mechanism to operate without indexes and allows server resources to be added on the fly. SiriDB's unique query language includes dynamic grouping of time series for easy and super fast analysis over large amount's of time series.

Gnocchi - Time series database

  •    Python

Gnocchi is an open-source |time series| database. The problem that Gnocchi solves is the storage and indexing of |time series| data and resources at a large scale. This is useful in modern cloud platforms which are not only huge but also are dynamic and potentially multi-tenant. Gnocchi takes all of that into account. Gnocchi has been designed to handle large amounts of aggregates being stored while being performant, scalable and fault-tolerant. While doing this, the goal was to be sure to not build any hard dependency on any complex storage system.