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Alex Spinov
Alex Spinov

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Quickwit Has a Free API: The Log Search Engine That Stores Petabytes on Object Storage at 1/10th the Cost of Elasticsearch

#quickwit #api #search #observability

Elasticsearch indexes everything in memory and local disks. That is fast but expensive — storing months of logs costs thousands per month. Quickwit indexes on object storage (S3, GCS), cutting costs by 90% while keeping search fast.

What Is Quickwit?

Quickwit is an open-source search engine for logs and traces. It stores indexes on object storage (S3, GCS, Azure Blob) instead of local disks, dramatically reducing infrastructure costs. It is Elasticsearch-compatible and can serve as a drop-in replacement for log analytics.

The Free Tool

Quickwit is completely free and open source:

  • Object storage: Indexes live on S3/GCS (pennies per GB)
  • Elasticsearch-compatible: ES-compatible API and query syntax
  • Sub-second search: Fast despite storage on S3
  • Schema-on-write: Structured and unstructured log search
  • OpenTelemetry: Native OTLP trace ingestion
  • Kafka integration: Ingest from Kafka topics
  • Grafana plugin: Query from Grafana dashboards
  • Jaeger integration: Distributed trace UI

Quick Start

Run Quickwit:

curl -L https://install.quickwit.io | sh
quickwit run
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Create an index:

curl -X POST http://localhost:7280/api/v1/indexes \
  -H 'Content-Type: application/yaml' \
  --data-binary '
version: 0.8
index_id: app-logs
search_settings:
  default_search_fields: [message, level]
doc_mapping:
  field_mappings:
    - name: timestamp
      type: datetime
      fast: true
      input_formats: [iso8601]
    - name: level
      type: text
      tokenizer: raw
    - name: message
      type: text
    - name: service
      type: text
      tokenizer: raw
  timestamp_field: timestamp
indexing_settings:
  merge_policy:
    type: stable_log
'
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Ingest logs:

curl -X POST http://localhost:7280/api/v1/app-logs/ingest \
  -H 'Content-Type: application/json' \
  --data-binary '
{"timestamp":"2026-03-28T10:00:00Z","level":"ERROR","message":"Connection refused to database","service":"api"}
{"timestamp":"2026-03-28T10:00:01Z","level":"INFO","message":"Retry successful","service":"api"}
'
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Search:

# Quickwit query syntax
curl 'http://localhost:7280/api/v1/app-logs/search?query=level:ERROR+AND+service:api&max_hits=10'

# Elasticsearch-compatible endpoint
curl -X POST 'http://localhost:7280/api/v1/_elastic/app-logs/_search' \
  -d '{"query":{"bool":{"must":[{"match":{"level":"ERROR"}},{"range":{"timestamp":{"gte":"2026-03-28"}}}]}}}'
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Why Teams Choose Quickwit

A SaaS company stored 6 months of logs in Elasticsearch: 12TB of data on 6 high-memory instances costing $4,200/month. After migrating to Quickwit backed by S3, the same data costs $140/month in S3 storage plus $200/month for a small compute instance. Search is slightly slower (2s vs 500ms) but perfectly acceptable for log analysis.

Who Is This For?

  • Platform teams drowning in Elasticsearch costs for logs
  • Companies needing long-term log retention without breaking the bank
  • DevOps teams wanting OpenTelemetry-native log storage
  • Anyone spending too much on log infrastructure

Start Saving on Logs

Quickwit gives you Elasticsearch-compatible search at object storage prices. Same queries, 90% less cost.

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