Grafana Loki vs DalmatinerDB

Struggling to choose between Grafana Loki and DalmatinerDB? Both products offer unique advantages, making it a tough decision.

Grafana Loki is a Monitoring & Observability solution with tags like logs, monitoring, observability.

It boasts features such as Log aggregation system, Optimized for querying logs, Uses labels to organize log streams, Integrates with Grafana for visualizations and pros including Open source and free, Scales horizontally, Fast queries, Integrated with Grafana ecosystem.

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.

Grafana Loki

Grafana Loki

Grafana Loki is an open source logging aggregation system designed to be part of the Grafana ecosystem. It is optimized for saving, indexing, and querying logs through labels and streams.

Categories:
Monitoring & Observability Logging
logs monitoring observability

Grafana Loki Features

  1. Log aggregation system
  2. Optimized for querying logs
  3. Uses labels to organize log streams
  4. Integrates with Grafana for visualizations

Pricing

  • Open Source

Pros

Open source and free

Scales horizontally

Fast queries

Integrated with Grafana ecosystem

Cons

Less features than commercial competitors

Steep learning curve

Not ideal for metrics storage

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