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Fast Time Series Database on Cassandra
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What is KairosDB?

KairosDB is a fast distributed scalable time series database written on top of Cassandra.
KairosDB is a tool in the Databases category of a tech stack.
KairosDB is an open source tool with 1.7K GitHub stars and 354 GitHub forks. Here’s a link to KairosDB's open source repository on GitHub

Who uses KairosDB?

3 companies reportedly use KairosDB in their tech stacks, including happn, waylay, and Energis.cloud.

13 developers on StackShare have stated that they use KairosDB.

KairosDB Integrations

Pros of KairosDB
As fast as your cassandra/scylla cluster go
Time-Series data analysis
Easy setup
Easy Rest API
Open source

KairosDB Alternatives & Comparisons

What are some alternatives to KairosDB?
InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand
It is a distributed, scalable time series database to store, index & serve metrics collected from computer systems at a large scale. It can store and serve massive amounts of time series data without losing granularity.
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.
See all alternatives

KairosDB's Followers
43 developers follow KairosDB to keep up with related blogs and decisions.