Axibase Time Series Database vs DalmatinerDB

Struggling to choose between Axibase Time Series Database and DalmatinerDB? Both products offer unique advantages, making it a tough decision.

Axibase Time Series Database is a Ai Tools & Services solution with tags like time-series, database, iot, devops, it-monitoring.

It boasts features such as Store and query numeric time series data, Analyze time series data using SQL queries, Visualize time series data using built-in graphing tools, Real-time aggregation and filtering of time series data, Rule-based alerting on time series, Plugin architecture to extend functionality, REST API for integration and pros including Purpose-built for time series data, High performance and scalability, Powerful analytics capabilities, Open source and free to use, Easy to set up and use.

On the other hand, DalmatinerDB is a Development product tagged with metrics, timeseries, erlang.

Its standout features include 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, and it shines with pros like Highly scalable and distributed architecture, Very fast writes for time-series data, Erlang runtime provides fault tolerance, Open source with permissive MIT license.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Axibase Time Series Database

Axibase Time Series Database

Axibase Time Series Database (ATSD) is an open-source time series database optimized for collecting, storing, analyzing, graphing, and visualizing numeric time series data. It is designed for IoT/DevOps/IT monitoring use cases.

Categories:
Ai Tools & Services Time Series Database
time-series database iot devops it-monitoring

Axibase Time Series Database Features

  1. Store and query numeric time series data
  2. Analyze time series data using SQL queries
  3. Visualize time series data using built-in graphing tools
  4. Real-time aggregation and filtering of time series data
  5. Rule-based alerting on time series
  6. Plugin architecture to extend functionality
  7. REST API for integration

Pricing

  • Open Source
  • Free
  • Subscription-Based

Pros

Purpose-built for time series data

High performance and scalability

Powerful analytics capabilities

Open source and free to use

Easy to set up and use

Cons

Limited to time series data only

Steep learning curve for full functionality

Limited ecosystem compared to more established databases

DalmatinerDB

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.

Categories:
Development Databases
metrics timeseries erlang

DalmatinerDB Features

  1. Fast write throughput
  2. Built-in sharding and replication
  3. Query language for analyzing time-series data
  4. HTTP API for writing and querying metrics
  5. 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