thanos

thanos / ex_datalog

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A pure Elixir Datalog engine with semi-naive fixpoint evaluation, stratified negation, provenance tracking, and telemetry.

10
0
100% credibility
Found Apr 22, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Elixir
AI Summary

ExDatalog is a pure Elixir library implementing a Datalog engine for building declarative programs with facts, rules, and relations to derive insights.

How It Works

1
📰 Discover ExDatalog

You hear about a smart tool that lets everyday apps uncover hidden patterns using simple rules and facts, like family trees or connections in data.

2
📦 Add to your app

You easily include the tool in your existing project so it can start reasoning right away.

3
📋 Set up your data

You describe groups for your information and add starting facts, like who is friends with whom.

4
Create discovery rules

You write straightforward rules that automatically find deeper insights, such as all ancestors or safe paths.

5
▶️ Run the reasoning

You launch the query and watch it compute new truths from your rules and facts.

Unlock new knowledge

Your app now reveals complete results, like full networks or predictions, ready to use with optional explanations of how they were found.

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Star Growth

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AI-Generated Review

What is ex_datalog?

ex_datalog is a pure Elixir Datalog engine for declarative querying over relations with recursion, stratified negation, and arithmetic ops like addition or comparisons. It handles graph traversals, fraud detection, or supply chain rules without external DBs, using a builder API to define relations, facts, and rules then query for derived results. Enable provenance to trace how facts derive, with telemetry for metrics.

Why is it gaining traction?

Stands out as a lightweight, pure Elixir datalogger ex—no NIFs or heavy deps—running efficiently via semi-naive fixpoint on datasets up to 100K facts. Pluggable storage and engines make it adaptable, while explainability and negation support real apps like social networks or LLM knowledge layers. Devs dig the zero-config install and structured results with pattern matching.

Who should use this?

Elixir backend devs building rule engines for fraud detection, graph reachability, or recursive aggregates in Phoenix apps. Suited for data engineers prototyping supply chains or infrastructure queries without graph DB overhead. Teams weaving Datalog into pure Elixir workflows for explainable inference.

Verdict

Worth a spin for Elixir recursive queries—excellent docs, 369 tests at 92% coverage, and v0.1 ships core features with ETS scaling ahead. Low 10 stars and 1.0% credibility mean it's pre-production; prototype first, monitor the roadmap.

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