Dontopedia

Qdrant

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

Qdrant has 19 facts recorded in Dontopedia across 3 references, with 2 live disagreements.

19 facts·15 predicates·3 sources·2 in dispute

Mostly:rdf:type(2), provides(2), has container id(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (3)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

hasRowHas Row(1)

mentionsMentions(1)

usesUses(1)

Other facts (17)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

17 facts
PredicateValueRef
Rdf:typeRetrieval System[2]
Rdf:typeVector Database[3]
ProvidesScalable Vector Search[3]
ProvidesPerformant Solution[3]
Has Container Id7eadd5459adb[1]
Uses Memory57.26MiB / 11.73GiB (0.48%)[1]
Uses Cpu0.19%[1]
Storage Size1150[2]
Scalability0.82[2]
Concurrency Support0.82[2]
Ease of Integration0.82[2]
Has Highest Storage Sizetrue[2]
Specializes inVector Search[3]
Competes WithMilvus[3]
Developed byQdrant Team[3]
Open Sourcetrue[3]
Use CaseScalable Search[3]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

hasContainerIdblah/resources/part-5
7eadd5459adb
usesMemoryblah/resources/part-5
57.26MiB / 11.73GiB (0.48%)
usesCpublah/resources/part-5
0.19%
typebeam/4faefe30-8af8-4236-991e-d38816071e57
ex:RetrievalSystem
labelbeam/4faefe30-8af8-4236-991e-d38816071e57
Qdrant
storageSizebeam/4faefe30-8af8-4236-991e-d38816071e57
1150
scalabilitybeam/4faefe30-8af8-4236-991e-d38816071e57
0.82
concurrencySupportbeam/4faefe30-8af8-4236-991e-d38816071e57
0.82
easeOfIntegrationbeam/4faefe30-8af8-4236-991e-d38816071e57
0.82
hasHighestStorageSizebeam/4faefe30-8af8-4236-991e-d38816071e57
true
typebeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
ex:VectorDatabase
labelbeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
Qdrant
providesbeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
ex:scalable-vector-search
providesbeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
ex:performant-solution
specializesInbeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
ex:vector-search
competesWithbeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
ex:milvus
developedBybeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
ex:qdrant-team
openSourcebeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
true
useCasebeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
ex:scalable-search

References (3)

3 references
  1. [1]Part 53 facts
    ctx:discord/blah/resources/part-5
  2. ctx:claims/beam/4faefe30-8af8-4236-991e-d38816071e57
    • full textbeam-chunk
      text/plain1 KBdoc:beam/4faefe30-8af8-4236-991e-d38816071e57
      Show excerpt
      matrix.loc['Sparse Retrieval', 'storage_size'] = 900 matrix.loc['Faiss', 'storage_size'] = 1100 matrix.loc['Hnswlib', 'storage_size'] = 1050 matrix.loc['Qdrant', 'storage_size'] = 1150 matrix.loc['DPR', 'scalability'] = 0.9 matrix.loc['Den
  3. ctx:claims/beam/65ffbfaa-762e-4210-bda5-5e222ad85a43

See also

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