Quickwit is an innovative, cloud-native search engine that excels in observability and is the perfect solution for managing logs and traces. Built as an open-source alternative to Datadog, Elasticsearch, Loki, and Tempo, Quickwit is optimized for search performance on cloud storage, offering unmatched speed and efficiency. By leveraging cutting-edge technologies like Rust and the Tantivy search engine library, Quickwit enables ultra-fast, sub-second search capabilities on large volumes of data stored in cloud environments. Its decoupled storage and compute architecture ensure optimal performance and cost-efficiency, making it a powerful tool for organizations looking to enhance their log and trace management solutions.
With Quickwit, you can seamlessly store and search your data on unlimited, cost-effective cloud storage, while benefitting from features like schemaless indexing and native OpenTelemetry and Jaeger support. Whether you’re troubleshooting errors or analyzing logs at scale, Quickwit delivers unparalleled performance with lower costs compared to traditional search technologies. Easily deployable on-premise or in Kubernetes environments, Quickwit integrates with popular object storage solutions (Amazon S3, MinIO, Ceph) and distributed queues (Apache Kafka, Amazon Kinesis), making it an ideal choice for modern observability needs.
Quickwit is powered by Tantivy, the fastest search engine library, and optimized with a smart I/O scheduling system that maximizes throughput. Written in Rust with no garbage collection, it provides vectorized processing and SIMD for lightning-fast search performance.
Quickwit enables you to search and troubleshoot logs and traces directly on unlimited, cost-efficient cloud storage. It provides sub-second search results and supports schemaless indexing, OpenTelemetry, and Jaeger for seamless integration.
Unlike traditional search engines designed for high queries per second (QPS), Quickwit excels at handling vast volumes of raw data with low QPS. Its architecture, built in Rust and Tantivy, ensures optimized CPU and processing power for executing queries directly on object storage.
By using object storage and a decoupled compute model, Quickwit enables limitless data storage without compromising performance, making it highly cost-effective compared to other search engines.
Quickwit is designed to be cloud-native, offering easy deployment on your existing infrastructure—whether on-premise or on Kubernetes. It integrates seamlessly with your choice of object storage solutions like Amazon S3, MinIO, or Ceph.
Quickwit can be easily plugged into distributed queues such as Apache Kafka and Amazon Kinesis, enabling efficient log and trace management and search in real-time across large-scale environments.
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