Cloud-native search engine for logs and traces on object storage.
Need to query massive volumes of historical log data without incurring massive storage costs.
Building custom, scalable observability pipelines that require high performance on cloud-native infrastructure.
Managing telemetry data at scale where decoupling storage from compute is a primary architectural requirement.
May find the infrastructure management overhead excessive compared to simple, managed SaaS logging services.
AI-powered tools that can replace or augment Quickwit
AI-powered observability platform that replaces Quickwit for high-volume log management and natural language querying via Axiom Copilot.
Cloud-native logging and observability for high-volume data.
AI-driven observability data lake that replaces Quickwit for automated log analysis, anomaly detection, and root cause identification.
Unified observability data lake for large-scale enterprise data.
AI-integrated observability platform that replaces Quickwit for unified log and trace analysis with natural language search and automated troubleshooting.
Open-source platform unifying logs, traces, and session replays.
Quickwit operates as an open-source project, offering a cost-efficient model that prioritizes low infrastructure spend by utilizing inexpensive object storage rather than traditional high-cost indexing nodes.
