What is the Elastic Stack?

The Elastic Stack (formerly the ELK Stack) is a collection of four core products: Elasticsearch (a search and analytics engine), Kibana (a visualization layer), Beats (lightweight data shippers), and Logstash (a data processing pipeline). Together, they form a powerful solution for ingesting, storing, searching, analyzing, and visualizing data in real time.

What is the difference between Elasticsearch and OpenSearch?

OpenSearch is an open-source fork of Elasticsearch and Kibana created by AWS and other partners in 2021. It was created in response to Elastic's decision to change its software license from the open-source Apache 2.0 license to the more restrictive Server Side Public License (SSPL). While they share a common origin, their development paths have now diverged, with each having its own unique features, governance, and community.

What are the main use cases for Elastic?

Elastic is used across three main solution areas: 1. Observability, for monitoring infrastructure and applications by analyzing logs, metrics, and APM traces. 2. Security, for threat hunting, security analytics (SIEM), and endpoint protection. 3. Enterprise Search, for building powerful search experiences for websites, applications, and internal documents.

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Elastic

Freemium

search engineobservabilitylog managementdata visualizationsiemapmdevopsbig datafull-text searchsecurity analytics

Elastic is a search-powered data platform offering a distributed analytics engine to power observability, security, and enterprise search solutions, enabling users to explore and analyze vast data volumes in real-time.

Try it out

Elastic provides a comprehensive suite of tools, known as the Elastic Stack, for ingesting, storing, searching, analyzing, and visualizing data at scale. Primarily serving developers, DevOps engineers, and security analysts, the platform is built around Elasticsearch, a powerful distributed search engine. Its unique value proposition lies in its combination of speed, scalability, and a unified platform for diverse use cases, from application performance monitoring to security information and event management (SIEM). This allows organizations to consolidate their observability, security, and search functionalities into a single, cohesive ecosystem. While the core is open source, Elastic offers managed cloud services and advanced features through a commercial subscription model.

Pros

Highly scalable and performant for real-time search and analytics across petabytes of data.
Comprehensive, integrated ecosystem (Elastic Stack) for ingest, visualization, and management.
Flexible and broad applicability across use cases including observability, security (SIEM), and enterprise search.
Powerful aggregation framework for complex analytics and data exploration.
Strong community and extensive documentation due to its open source origins.

Cons

Can have a steep learning curve, especially for cluster administration, query optimization, and scaling.
Resource-intensive, requiring significant memory and CPU which can lead to high operational costs.
Complex, consumption-based cloud pricing can be difficult to predict and manage.
Licensing changes to the Server Side Public License (SSPL) have created friction and confusion in the open source community.

Key features

Elasticsearch: A distributed, RESTful search and analytics engine.
Kibana: A data visualization and exploration tool for dashboards and UI.
Logstash and Beats: Server-side data processing pipeline and single-purpose data shippers.
Unified Observability: Combines logs, metrics, APM traces, and uptime monitoring.
Elastic Security: Provides SIEM, endpoint security, and threat hunting capabilities.
Enterprise Search: Tools to create search experiences for websites, apps, and workplace content.
Vector Search and ML: Capabilities for semantic search, recommendations, and other AI-powered applications.

Integrations

Amazon Web Services (S3, Kinesis)Google Cloud Platform (GCS, Pub/Sub)Microsoft Azure (Event Hubs, Blob Storage)Kubernetes & DockerApache KafkaPrometheusNGINXPostgreSQLMongoDB

Target audience

Developers, DevOps engineers, Site Reliability Engineers (SREs), security analysts, and data engineers needing to build powerful search, observability, or security solutions.

Ratings & Reviews

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Key Metrics

Founded

2012

Headquarters

Amsterdam, Netherlands & Mountain View, USA

Pricing Tiers

Free

Basic deployment on Elastic Cloud with limited compute, storage, and memory. Includes core Elastic Stack features for small-scale projects and learning.

Free

Standard

Recommended for most use cases, adding features like machine learning, alerting, and full technical support. Pricing is based on resource consumption.

$95/mo

Gold

Includes all Standard features plus additional capabilities like reporting and enhanced support options. Geared towards business-critical applications.

Custom

Platinum

Includes all Gold features, plus advanced security controls like document-level and field-level security, and the highest level of support.

Custom

Enterprise

All Platinum features with additional benefits like private link connectivity, support for Federal and classified environments, and custom plugin support.

Custom

Frequently Asked Questions

Top Alternatives to Elastic

Splunk

A mature and powerful competitor in the SIEM and observability space, often chosen for its extensive enterprise feature set and app ecosystem, though typically at a higher price point.

OpenSearch

A fully open-source option for users who want to avoid Elastic's licensing and prefer a community-driven project with a similar feature set at its core.

Datadog

A leading SaaS-based observability platform known for its ease of use, strong APM capabilities, and seamless integration of metrics, traces, and logs.

Grafana Stack (Loki)

A popular open-source alternative for observability, often chosen for its powerful visualization (Grafana) and cost-effective log aggregation solution (Loki).

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