Quickwit

Overview

Quickwit is a cloud-native search engine designed specifically for observability data, providing an open-source alternative to Datadog, Elasticsearch, Loki, and Tempo. Built in Rust on the Tantivy search library, Quickwit offers petabyte-scale log management and distributed tracing capabilities.

Key Features

Cloud-Native Architecture

• Decouples compute from storage
• Indexes stored in object storage (S3, GCS, etc.)
• Searchers are stateless and scale independently
• Sub-second search latency on data in object storage

Performance & Scalability

• Handles petabyte-scale data with minimal infrastructure
• Often requires just a few nodes for massive datasets
• 10x cost efficiency over alternatives like Elasticsearch or Datadog
• Fast query execution through smart indexing and distributed processing

Observability Support

• Native support for OpenTelemetry, Jaeger, and Elasticsearch-compatible APIs
• Tailored for log management and distributed traces
• Supports both schemaless ingestion (JSON logs) and strict schemas
• Dynamic fields and automatic schema discovery

Use Cases

• Log Management: High-performance log search and analytics
• Distributed Tracing: OpenTelemetry and Jaeger trace storage and search
• Observability: Centralized observability platform for monitoring and debugging
• Cost Optimization: Reduce observability costs while maintaining performance

Technical Details

Built on Tantivy

• Leverages the fast Rust search engine library for indexing and queries
• Provides full-text search capabilities optimized for time-series data
• Supports complex query patterns and aggregations

Data Ingestion

• Supports schemaless ingestion for flexibility
• Strict schemas available for structured data
• Automatic schema discovery for JSON documents

Recent Developments

In January 2025, Datadog acquired Quickwit to boost real-time observability capabilities. Quickwit remains open-source, continuing to aid industries with strict data regulations.

Pricing

Open-source and free to use, with up to 10x lower costs compared to commercial alternatives like Elasticsearch or Datadog for equivalent workloads.