dingo
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.
Not yet testedsource: GitHubhomepageJavaApache-2.0commit bb96a7414c86
Java, Apache-2.0 licensed. The project labels itself: embedding search, embedding store, hybrid search, key value distributed store, mysql compatibility, real time semantic search, serving and structured data.
dingo has not been verified yet.
Measured by Argusic on a fresh machine every time. Every number links to its evidence.
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
No recorded runs.
Topics (from GitHub)
embedding-searchembedding-storehybrid-searchkey-value-distributed-storemysql-compatibilityreal-time-semantic-searchservingstructured-dataunified-sqlunstructured-datavector-databasevector-ocean
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/dingo)Questions
- Does dingo run?
- dingo has not been fully verified yet. No recorded run has produced a verdict yet.
- How did Argusic test dingo?
- On a fresh, disposable machine, with every command recorded. 0 attempts are recorded, and the full method is on the methodology page.
- Where is the evidence for dingo?
- All 0 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.