Ghost DB
Ghost DB is an open-source database platform optimized for managing large volumes of time-series data. It is horizontally scalable, high performance, and has a query engine and visualization tools designed specifically for handling time-series data.
timeseries
scalable
highperformance
visualization
Ghost DB: Open-Source Time-Series Database
An open-source database platform optimized for managing large volumes of time-series data, with horizontal scalability, high performance and visualization tools
What is Ghost DB?
Ghost DB is an open-source time-series database optimized for managing large volumes of temporal data efficiently. It is purpose-built for handling time-stamped records like server metrics, application performance monitoring data, IoT sensor data, and industrial telemetry.
Some key features and benefits of Ghost DB include:
- Horizontally scalable architecture that allows linear scaling of reads and writes as nodes are added.
- High write throughput and compression algorithms to support ingesting and storing billions of data points.
- Fast queries across terabytes of recent time-series data by automatically partitioning data across nodes.
- Data retention policies to store historical data cost-efficiently in cheaper storage tiers.
- Visualization and charting tools for time-series analytics built-in.
- Support for collecting and storing data from a variety of sources such as applications, devices, and cloud services.
- RESTful API for easy integration and administration.
Overall, Ghost DB excels in collecting, storing, analyzing, and visualizing operational time-series data at scale. Its unique architecture optimizes it specifically for time-stamped use cases across industries like IoT, DevOps, infrastructure monitoring, and industrial telemetry.
Ghost DB Features
Features
- Horizontally scalable architecture
- Optimized for time-series data
- High performance write throughput
- Built-in query engine and visualization tools
- Open source under Apache license
Pricing
- Open Source
Pros
Handles large volumes of time-series data efficiently
Easy horizontal scaling
Fast write performance
Purpose-built for time-series use cases
Free and open source
Cons
Limited to time-series data only
Less flexible than general purpose databases
Lacks some features of commercial databases
Official Links
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