KairosDB
KairosDB is a fast, scalable, open source time series database that is designed to analyze large amounts of time-stamped data. It is written in Java and built on top of Cassandra for high scalability and performance.
KairosDB: Fast Open Source Time Series Database
A scalable time series database designed to analyze large amounts of time-stamped data, built on Cassandra for high performance and scalability.
What is KairosDB?
KairosDB is an open source distributed time series database written in Java that is designed to efficiently store and query massive amounts of time-series data. It is built on top of Apache Cassandra to leverage its scalability and high availability.
Some key features of KairosDB include:
- High write throughput to handle large volumes of time-series data
- Advanced querying through predicates and groupby functions
- Tagging for faster queries and easier management of similar metrics
- Downsampling for data retention over long periods
- Pluggable storage engines, allowing other databases like H2 to be used for storage
- Web UI and REST API for easy access and integration
- Horizontal scalability through Cassandra's distributed architecture
KairosDB is commonly used for IoT applications, metrics collection and monitoring, analytics, and other time-series data use cases. Its flexibility and scalability make it well suited for modern big data applications.
KairosDB Features
Features
- Scalable time series data storage
- High performance write and query operations
- Plugin architecture for custom data processing
- Integration with Cassandra for distributed storage
- REST API for data access
- Aggregation functions for time series data analysis
Pricing
- Open Source
Pros
Highly scalable to handle large time series data
Fast write performance for ingesting high velocity data
Flexible query capabilities
Easy to deploy and manage
Integrates with existing Cassandra clusters
Open source with active development community
Cons
Limited ad-hoc analytics compared to full analytics databases
Less ecosystem support than more established databases
Requires expertise with Cassandra for production deployments
Not ideal for complex time series modeling
Official Links
Reviews & Ratings
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