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Kikiola

Kikiola is a Go vector database that stores, indexes and searches high-dimensional vectors for similarity and retrieval applications.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Kikiola — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Kikiola when an application needs a self-hosted database layer for vector storage, similarity search or embedding retrieval.

Who it is for

  • Developers building embedding-based search or recommendation features.
  • Teams assembling retrieval systems that need a vector-storage layer.

Documented uses

  • Store and index document embeddings for semantic retrieval.
  • Search vectors using text-based queries and rerank results with relevance scores.
  • Index multilingual embeddings or vectors representing documents, images, audio and video.
Before you choose

Requirements & limits

The repository is public and licensed under MIT. The README documents a local server run using Go.

  • Kikiola stores and searches vectors; embedding generation is a separate workflow, with repository tutorials linking to example generation-and-storage workflows.
  • The README lists tensor compression, concurrent writes and multi-node or sharded storage, but does not provide performance or scaling guarantees in the cited description.
  • The project is written in Go and describes an API for application integration.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Build and start the local Kikiola server

Compile the repository and start its documented local server.

Before you start

  • Go installed
  • A shell environment

Steps

  1. Clone the repository with the command below.

    Documented command
    git clone https://github.com/0xnu/kikiola.git

  2. Change into the project directory with cd kikiola.

  3. Build the project with the command below.

    Documented command
    go build ./...

  4. Start the server with the command below.

    Documented command
    go run cmd/main.go

Expected outcome

The README says the server starts at http://localhost:3400.

Guide limitations

  • This setup procedure does not cover configuring a production deployment.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Vector search

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
KikiolaStore and index document embeddings for semantic retrieval.Docker, Self-hosted, ServerThe repository is public and licensed under MIT. The README documents a local server run using Go.
MettisIndex text documents through an HTTP endpoint.Linux, Self-hosted, Server
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
0xnu/kikiola · Official homepage title · retained in its source language
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