Scalyr vs Logstash

Struggling to choose between Scalyr and Logstash? Both products offer unique advantages, making it a tough decision.

Scalyr is a Ai Tools & Services solution with tags like logging, monitoring, observability, troubleshooting, incident-response.

It boasts features such as Real-time log management and search, Advanced filtering and correlation, Customizable dashboards and alerts, Automatic parsing and enrichment, Kubernetes and microservices monitoring, Anomaly detection and forecasting, Role-based access control and pros including Fast and scalable log ingestion, Powerful query language and analytics, Easy dashboard creation, Integrates well with Kubernetes, Good value for money.

On the other hand, Logstash is a Network & Admin product tagged with logging, etl, data-processing.

Its standout features include Real-time pipeline processing, Plugin ecosystem for inputs, filters, outputs, Built-in web interface, Centralized logging pipeline, Elasticsearch integration, Kibana integration for data visualization, and it shines with pros like Open source and free, Scalable and distributed, Large plugin ecosystem, Powerful log processing capabilities, Integrates well with Elasticsearch stack.

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.

Scalyr

Scalyr

Scalyr is a log management and observability platform designed for monitoring, troubleshooting, and securing cloud-native infrastructure and applications. It ingests logs, metrics, and events to provide visibility into systems and enable faster incident response.

Categories:
logging monitoring observability troubleshooting incident-response

Scalyr Features

  1. Real-time log management and search
  2. Advanced filtering and correlation
  3. Customizable dashboards and alerts
  4. Automatic parsing and enrichment
  5. Kubernetes and microservices monitoring
  6. Anomaly detection and forecasting
  7. Role-based access control

Pricing

  • Subscription-Based

Pros

Fast and scalable log ingestion

Powerful query language and analytics

Easy dashboard creation

Integrates well with Kubernetes

Good value for money

Cons

Steep learning curve

Can get expensive for large volumes of data

Limited native integrations

No long-term log archiving


Logstash

Logstash

Logstash is an open source data processing pipeline that ingests data from multiple sources, transforms it, and then sends it to a destination. It is used for collecting, parsing, and storing logs for future use.

Categories:
logging etl data-processing

Logstash Features

  1. Real-time pipeline processing
  2. Plugin ecosystem for inputs, filters, outputs
  3. Built-in web interface
  4. Centralized logging pipeline
  5. Elasticsearch integration
  6. Kibana integration for data visualization

Pricing

  • Open Source

Pros

Open source and free

Scalable and distributed

Large plugin ecosystem

Powerful log processing capabilities

Integrates well with Elasticsearch stack

Cons

Steep learning curve

Resource intensive

Complex configuration

Not optimized for analytics