Home/Compare/aquila vs search

Comparison

aquila vs search

Verdict

Pick aquila if aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches; pick search if search is a Go library enabling embedded vector search and semantic embeddings via the llama.cpp framework.

Markdown twin · aquila alternatives · search alternatives

GraphCanon updated 1d

aquila logo

aquila

Aquila-Network/aquila

379pushed May 6, 2024
vs
search logo

search

kelindar/search

558pushed Mar 6, 2026

Trust & integrity

Signalaquilasearch
Maintenance
Dormant (817d since push)
As of 3w · github_public_v1
Slowing (169d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Personal account
As of 1d · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

aquila
Efficient Neural Search Engine
search
Go library for embedded vector search and semantic embeddings with llamacpp

Stars

aquila
379
search
558

Forks

aquila
26
search
24

Open issues

aquila
13
search
5

Language

aquila
HTML
search
Go

Adopt for

aquila
Aquila is an efficient neural search engine designed for indexing latent vectors and JSON metadata while performing k-NN searches.
search
search is a Go library enabling embedded vector search and semantic embeddings via the llama.cpp framework.

Persona

aquila
-
search
-

Runtime

aquila
-
search
-

License

aquila
-
search
MIT

Last pushed

aquila
May 6, 2024
search
Mar 6, 2026

Categories

aquila
Data & Retrieval, Vector Databases
search
Data & Retrieval, Vector Databases

Trust and health

Maintenance

aquila
Dormant (18%)
search
Slowing (36%)

Days since push

aquila
817d
search
169d

Open issues (now)

aquila
13
search
5

Stars delta

aquila
Unknown
search
+3 (30d)

Open issues delta

aquila
Unknown
search
0 (30d)

Owner type

aquila
Organization
search
User

Full report

Choose aquila if…

  • aquila is primarily HTML; search is Go.
  • Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors.
  • When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary

When NOT to use aquila

  • If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration
  • In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide

Choose search if…

  • search is primarily Go; aquila is HTML.
  • Tags unique to search: ai, bert, embeddings, gguf.
  • Use for projects needing a lightweight, fast integration of semantic search capabilities within applications written in Go

When NOT to use search

  • Avoid if relying on out-of-the-box support beyond Go or requiring heavy customization that is not supported directly by llama.cpp's capabilities
  • Not suitable when a more comprehensive database service with extensive querying and integration features is desired over an embedded solution

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: aquila 379 · search 558 (synced Aug 2, 2026).

Common questions

What is the difference between aquila and search?
aquila: Efficient Neural Search Engine. search: Go library for embedded vector search and semantic embeddings with llamacpp. See the comparison table for live GitHub stats and shared categories.
When should I choose aquila over search?
Choose aquila over search when aquila is primarily HTML; search is Go; Tags unique to aquila: approximate-nearest-neighbor-search, embedding, faiss, feature-vectors; When deploying a solution that requires the processing of feature vectors in image or video search contexts, where efficiency in approximate nearest neighbor search is necessary.
When should I choose search over aquila?
Choose search over aquila when search is primarily Go; aquila is HTML; Tags unique to search: ai, bert, embeddings, gguf; Use for projects needing a lightweight, fast integration of semantic search capabilities within applications written in Go.
When should I avoid aquila?
If the development team lacks experience with Docker, as Aquila's setup heavily relies on Docker images to run locally or in a big data configuration In scenarios where strict control over metadata and vector indexing is required beyond what JSON and latent vectors can provide
When should I avoid search?
Avoid if relying on out-of-the-box support beyond Go or requiring heavy customization that is not supported directly by llama.cpp's capabilities Not suitable when a more comprehensive database service with extensive querying and integration features is desired over an embedded solution
Is aquila or search more popular on GitHub?
search has more GitHub stars (558 vs 379). Stars measure visibility, not whether either tool fits your constraints.
Are aquila and search open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to aquila or search?
GraphCanon lists graph-backed alternatives at aquila alternatives and search alternatives (aquila markdown twin, search markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, aquila or search?
aquila: Dormant. search: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for aquila and search?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: aquila trust report; search trust report.

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