Quickwit
FREEMIUMLightning-fast search for massive datasets
► Large-scale log and event data search
Product Details
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PROS & CONS
STRENGTHS
- Excellent performance for large, immutable datasets.
- Impressive query performance on large datasets due to its architectural design.
- Extremely cost-effective storage using cloud object stores.
WEAKNESSES
- −Younger ecosystem with fewer integrations and a smaller community than established alternatives like Elasticsearch.
- −Primarily optimized for immutable data, less ideal for frequent updates.
KEY FEATURES
Object storage native
Built to work directly with cost-effective S3-like storage (S3, MinIO, etc.).
Object Storage Native
Indexes directly on S3, GCS, or Azure Blob for low cost.
Log and trace analytics
Specialized for observability use cases like log, trace, and event data.
Sub-second search
Delivers fast query responses on massive datasets using indexing and caching.
WHO IS Quickwit BEST FOR?
Data engineers and analysts
They require a scalable, cloud-native search engine to index and query large-scale datasets like application events or clickstreams directly from object storage.
DevOps and SRE teams
They need to ingest and search high-volume logs (like Kubernetes or application logs) in real-time with low cost and high performance.
INTEGRATIONS
TECHNICAL DETAILS
✓ REST
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