Showing 4 open source projects for "elasticsearch"

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  • 1
    Qdrant

    Qdrant

    Vector Database for the next generation of AI applications

    ... functionality. Implement a unique custom modification of the HNSW algorithm for the Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results. Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values. Unlike Elasticsearch post-filtering, Qdrant guarantees all relevant vectors are retrieved.
    Downloads: 8 This Week
    Last Update:
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  • 2
    OpenObserve

    OpenObserve

    Elasticsearch/Splunk/Datadog alternative for (logs, metrics, traces)

    OpenObserve is a cloud-native observability platform built specifically for logs, metrics, traces, and analytics designed to work at a petabyte scale. It is very simple and easy to operate as opposed to Elasticsearch which requires a couple of dozen knobs to understand and tune which you can get up and running in under 2 minutes. It is a drop-in replacement for Elasticsearch if you are just ingesting data using APIs and searching using Kibana (Kibana is not supported nor required...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Quickwit

    Quickwit

    Sub-second search & analytics engine on cloud storage

    Sub-second search & analytics engine on cloud storage. Quickwit is the fastest search engine on cloud storage. Quickwit has an Elasticsearch-compatible Ingest-API to make it easier to migrate your log shippers (Vector, Fluent Bit, Syslog, ...) to Quickwit. However, we only support ES aggregation DSL, the query DSL support is planned for Q2 2023. The core difference and advantage of Quickwit are its architecture built from the ground to search on cloud storage. We optimized IO paths, revamped...
    Downloads: 0 This Week
    Last Update:
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  • 4
    Sonic

    Sonic

    Fast, lightweight & schema-less search backend

    Sonic is a super fast and lightweight, schema-less search backend that can be used in place of super-heavy and full-featured search backends like Elasticsearch. It is able to normalize language search queries, auto-complete search queries and offer the most relevant results. Being an identifier index rather than a document index, when queried it provides IDs that can be used to refer to matched documents in an external database.
    Downloads: 0 This Week
    Last Update:
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