PomaiDB Python Bindings
Official Python bindings for PomaiDB, an embedded vector database designed for high-performance Edge AI applications.
Installation
pip install pomaidb
Quick Start
import pomaidb
# 1. Open database
db = pomaidb.open_db("test_db", dim=4)
# 2. Put vectors
db.put(1, [1.0, 0.0, 0.0, 0.0])
db.put(2, [0.0, 1.0, 0.0, 0.0], membrane="docs", payload=b"doc_payload", timestamp=1000)
# 3. Search
hits = db.search([1.0, 0.0, 0.0, 0.0], topk=5)
for hit in hits:
print(f"ID: {hit.id}, Score: {hit.score}")
# 4. Multi-membrane query
hits_docs = db.search([0.0, 1.0, 0.0, 0.0], topk=5, membrane="docs")
# 5. Flush and close
db.flush()
db.close()
Features
- In-process embedded execution (zero network overhead, zero configuration).
- Pomegranate Engine Architecture: Rind MemTable, Locule immutable containers, and Press compaction.
- Built-in Quantization: FP32, SQ8, FP16, 1-bit binary quantization, PQ8.
- Native multi-membrane tenancy and arbitrary payload buffering.
1 maintainer
Metadata
1 maintainer
Release files for pomaidb 0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pomaidb-0.2.1.tar.gz | 2.3 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pomaidb-0.2.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.6 MB
Release files / pomaidb-0.2.1.tar.gz
| Download URL | pomaidb-0.2.1.tar.gz |
|---|---|
| Size | 2.3 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.16
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Release files / pomaidb-0.2.1-py3-none-any.whl
| Download URL | pomaidb-0.2.1-py3-none-any.whl |
|---|---|
| Size | 2.3 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.16
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