DalmatinerDB
DalmatinerDB is a fast, distributed metrics database written in Erlang. It is optimized for storing time-series data like metrics and events. It can handle high volumes of writes with low latency.
metrics
timeseries
erlang
DalmatinerDB: Fast Distributed Metrics Database
DalmatinerDB is a fast, distributed metrics database written in Erlang. It is optimized for storing time-series data like metrics and events. It can handle high volumes of writes with low latency.
What is DalmatinerDB?
DalmatinerDB is an open-source, high-performance metrics database and time-series database (TSDB) written in Erlang. It is designed to collect, store and query large volumes of time-series data with millisecond precision.
Some key features and benefits of DalmatinerDB include:
- Fast writes - Optimized to handle high velocity data with minimal latency. Can handle hundreds of thousands of data points per second.
- Scalability - Runs distributed on multiple nodes with automatic data partitioning and replication. Scales horizontally to handle increasing data volumes.
- Reliability - Data is replicated for fault-tolerance. Continues operation during node failures or network partitions.
- Query performance - Fast aggregation operations on large data sets. Uses probabilistic data structures for efficiency.
- Ease of use - Intuitive query language and API bindings provided for various languages. Easy to set up and operate.
- Visualization - Plays well with Grafana for building dashboards to visualize metrics.
- Open source - Released under the LGPLv3 license. Transparent code and helpful community.
DalmatinerDB is well-suited for applications that need to collect, analyze and monitor high-frequency performance or business metrics at scale. Common use cases include infrastructure monitoring, IoT sensor data, network analytics, application performance management, business intelligence and analytics, etc.
DalmatinerDB Features
Features
- Fast write throughput
- Built-in sharding and replication
- Query language for analyzing time-series data
- HTTP API for writing and querying metrics
- Plugins for ingesting data from various sources
Pricing
- Open Source
Pros
Highly scalable and distributed architecture
Very fast writes for time-series data
Erlang runtime provides fault tolerance
Open source with permissive MIT license
Cons
Limited query capabilities compared to full-featured databases
Lacks some features of commercial time-series databases
Smaller community than more popular databases
Official Links
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