While searching the perfect database for my project, I spent hours and hours searching the internet and making a list of all candidates. Quickly I realized that the list is pretty long and the projects differ in many ways, but all of the have the same goal: store your time series data.
How the data looks like
The structure of time series data always consists of at least 2 parts (we call it a datapoint): time and value. At certain time we have a certain value. Based on architecture of different time series databases, we also annotate the datapoint with additional information. The goal of the information is to better differentiate the data and filter it easier. One of the examples is adding source=device.1 tag to the datapoint. Later we can easily fetch all the data that belongs to device.1.
So in some context, time series databases are similar to key-value databases where key is combination of time and tags. Only difference is, that we have a better ability to filter the data and all the nice aggregations functions (min, max, avg, dev, ..) are already built in (well in most cases). As with key-value databases everything starts with a key, in time series databases everything starts with time.
Below is the list of all the time series databases I found that follow the previous mentioned principle. If you find a new unlisted database or you create a new one and want to share, send me an email at erol@(enter my domain name).
The list
1. OpenTSDB
Website: http://www.opentsdb.net/
Pricing: Free
Technologies: Java, HBase
Presentation: http://youtu.be/WlsyqhrhRZA
Store and serve massive amounts of time series data without losing granularity.
2. KairosDB
Website: http://www.kairosdb.org
Pricing: Free
Technologies: Java, Cassandra
Clients: Java, Python
Presentation: http://youtu.be/Ykf_C9RZEQI?t=31m15s
KairosDB is a fast distributed scalable time series database written on top of Cassandra.
3. InfluxDB
Website: http://influxdb.com/
Pricing: Free
Technologies: Go, BoltDB
Clients: JavaScript, Ruby, Python, Node.js, PHP, Java, Clojure, Common Lisp, Go, Scala, R, Erlang, Perl, Haskell, .NET
Presentation: http://youtu.be/sRi64imN7xg
InfluxDB is a time series, metrics, and analytics database. It’s written in Go and has no external dependencies. That means once you install it there’s nothing else to manage (like Redis, ZooKeeper, HBase, or whatever).
4. TempoIQ
Website: https://www.tempoiq.com/
Pricing: Subscription
Clients: .NET, Java, Node.js, Python, Ruby
Presentation: http://youtu.be/TRv0tfFAdbY
Fast, scalable monitoring & analysis of sensor data in your application.
5. Graphite
Website: https://github.com/graphite-project
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 database. The data can then be visualized through graphite’s web interfaces.
6. Druid
Website: http://druid.io/
Pricing: Free
Technologies: Java
Clients: Ruby, Python, R, Node.js
Presentation: http://youtu.be/Dlqj34l2upk
An open-source, real-time data store designed to power interactive applications at scale.
7. kdb+
Website: http://kx.com/
Technologies: K
Clients: Java, .NET, Python, Excel
Presentation: http://youtu.be/AGGGU7tVdEk
The high-performance database that sets the standard for time-series analytics.
8. RRDtool
Website: http://oss.oetiker.ch/rrdtool/
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.
9. seriesly
Website: https://github.com/dustin/seriesly
Technologies: Go
seriesly is a database for storing and querying time series data. Unlike databases like RRDtool, it’s schemaless so you can just lob data into it and start hacking. However, it also doesn’t use a finite amount of space.
10. Cube
Website: http://square.github.io/cube/ (development seems stopped, most active fork is https://github.com/red-gate/cube)
Pricing: Free
Technologies: Node.js, MongoDB
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. Cube is built on MongoDB.
11. IBM Informix
Website: http://www-01.ibm.com/software/data/informix/
Informix, with its TimeSeries feature, helps organizations solve the Big Data challenge of sensor data by providing unprecedented performance and scalability to applications that leverage time series data.
12. Akumuli
Website: http://www.akumuli.org/
Pricing: Free
Technologies: C++
Distributed time-series database
13. BlueFlood
Website: http://blueflood.io/
Technologies: Java
Presentation: http://vimeo.com/87210602
Blueflood is a multi-tenant distributed metric processing system created by engineers at Rackspace. It is used in production by the Cloud Monitoring team to process metrics generated by their monitoring systems. Blueflood is capable of ingesting, rolling up and serving metrics at a massive scale.
14. DalmatinerDB
Website: https://dalmatiner.io/
Technologies: Erlang, ZFS, Riak Core
DalmatinerDB is a no fluff purpose built metric database. Not a layer put on top of a general purpose database or datastores.
15. Rhombus
Website: https://github.com/Pardot/Rhombus
Pricing: Free
Technologies: Java, Cassandra
A time-series object store for Cassandra that handles all the complexity of building wide row indexes.
16. Prometheus
Website: http://prometheus.io/
Pricing: Free
Technologies: Go
Clients: Go, Java, Ruby
An open-source service monitoring system and time series database.
17. Axibase Time-Series Database
Website: http://axibase.com/products/axibase-time-series-database/
Pricing: Free & License version
Technologies: Java, HBase, Hadoop
Clients: Java, R Language, PHP, Python, Ruby, JavaScript
Axibase Time-Series Database (ATSD) is a next-generation statistics database. ATSD is for companies that need to extract value from large amounts of time-series data which exists in their IT and operational infrastructure.
18. Newts
Website: http://opennms.github.io/newts/
Pricing: Free
Technologies: Java, Cassandra
A time-series data store based on Apache Cassandra.
19. InfiniFlux
Website: http://www.infiniflux.com/
Pricing: Free & License version
Technologies: C
Clients: Java, Python, JavaScript, R, PHP
INFINIFLUX is the World’s Fastest Time Series DBMS for IoT and BigData.
20. Heroic
Website: https://spotify.github.io/heroic/
Pricing: Free
Technologies: Java, Cassandra, Elasticsearch
The Heroic Time Series Database
21. Riak TS
Website: http://basho.com/products/riak-ts/
Pricing: Free & License version
Technologies: Erlang
Clients: Java, Ruby, Python, Erlang, Node.js
Presentation: https://www.youtube.com/watch?v=l-U-oSnpdLQ
Riak TS is the only enterprise-grade NoSQL database optimized for IoT and Time Series data
22. The Warp 10 Platform
Website: http://www.warp10.io/
Pricing: Free
Technologies: Java, WarpScript
Presentation: http://www.slideshare.net/Mathias-Herberts/warp-10-platform-presentation-criteo-beer-tech-20160203
Warp 10 is an Open Source Geo Time Series® Platform designed to handle data coming from sensors, monitoring systems and the Internet of Things.
23. KsanaDB
Website: https://github.com/zzzmanzzz/KsanaDB
Pricing: Free
Technologies: Go, Redis
KsanaDB is a time series database, base on redis and go.
24. eXtremeDB DBMS
Website: http://financial.mcobject.com/
Pricing: License version
Presentation: https://youtu.be/lG7Fw1sHFKQ
The eXtremeDB DBMS product family delivers high levels of scalability, reliability and processing speed for storing and manipulating complex data, and is used successfully in environments ranging from Big Data analytics in the data center to supporting increasingly “smart” features in the resource-constrained devices comprising the Internet of Things.
25. SiriDB
Website: http://siridb.net/
Pricing: Free
Technologies: C
SiriDB is a highly-scalable, robust and fast time series database. Build from the ground up SiriDB uses a unique mechanism to operate without a global index and allows server resources to be added on the fly. SiriDB’s unique query language includes dynamic grouping of time series for easy analysis over large amounts of time series.
26. DB4IoT
Website: http://db4iot.com/
Pricing: License version
Presentation: https://youtu.be/X-4OB_8SzTI
Visualize and analyze time-series IoT data with blazing-fast interactive maps for the
“Internet of Moving Things.”
27. quasardb
Website: http://www.quasardb.net/
Pricing: Client API Open Source, Community Edition and Enterprise Edition
Technologies: C++14
Clients: Java, .NET, Python, Excel, C, C#, C++, R
Quasardb is a high-performance, distributed, column-oriented database with native time series support.
I will frequently update the list and add new time series databases as they come along.
