luizferreira-io

luizferreira-io / ellie

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PostgreSQL performance tuning tool

19
1
89% credibility
Found May 20, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

Ellie is a terminal-based PostgreSQL monitoring and tuning tool that connects to your database and displays real-time health information through colorful dashboards. It shows metrics like cache hit ratios, active sessions, transactions, locks, and conflicts. The tool includes 18 different performance analyses covering disk usage, table fragmentation, indexing issues, shared buffer usage, and slow queries. You can browse all active connections, view configuration settings, and identify optimization opportunities—all from a clean interface that runs directly in your terminal.

How It Works

1
🔍 You hear about a database monitoring tool

A developer friend tells you about Ellie, a tool that shows your PostgreSQL database health right in your terminal.

2
📦 You download and run it

You grab the ready-made version for your computer, unzip it, and run it directly from your terminal.

3
🔗 You connect to your database

You enter your database server address, username, and password. Ellie connects and starts gathering information.

4
📊 Your dashboard comes alive

A colorful dashboard fills your screen showing real-time charts of cache performance, active sessions, transactions, and locks.

5
🔎 You explore your database activity

You switch to the Activity tab to see every connection, what queries are running, and which ones are waiting for something.

6
You dive into performance tuning
💾
Check disk space

See which tablespaces, schemas, and tables are using the most storage.

📏
Find bloated tables

Discover tables with too much wasted space that need vacuuming.

🔍
Spot missing indexes

Find tables doing full scans that could benefit from indexes.

✅ You understand your database

With all this insight, you know exactly where to focus your optimization efforts and keep your database running smoothly.

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Star Growth

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AI-Generated Review

What is ellie?

Ellie is a terminal-based PostgreSQL performance monitoring and tuning tool built in Rust. It connects to a PostgreSQL server and renders a real-time interactive dashboard showing server health, active sessions, configuration parameters, and detailed performance analysis. You launch it from the command line with connection flags or a full URL, and it immediately surfaces metrics like cache hit ratios, transaction rates, lock contention, and session counts. The Tuning tab runs 18 structured analyses across disk allocation, table fragmentation, indexing, shared buffers, and query performance. It requires PostgreSQL 10 or later and optionally uses pg_stat_statements and pg_buffercache extensions for deeper insights.

Why is it gaining traction?

Unlike heavy GUI tools or browser-based dashboards, Ellie lives entirely in your terminal and starts instantly. The interface is surprisingly polished for a Rust CLI: you get tabbed navigation, sortable tables, adjustable column widths, and ASCII charts for metrics over time. The five-category tuning system gives DBAs a structured way to spot bloated tables, missing indexes, and slow queries without writing raw SQL. Pre-compiled binaries ship for Linux and Windows, so no Rust toolchain is required to run it.

Who should use this?

PostgreSQL DBAs who live in the terminal and want a quick health snapshot without spinning up pgAdmin. DevOps engineers debugging performance issues on remote servers where GUI tools are impractical. Developers maintaining small to medium PostgreSQL deployments who need visibility into shared buffers, query performance, and autovacuum activity without configuring external monitoring stacks.

Verdict

Ellie is a promising early-stage tool with a clear niche: lightweight, terminal-first PostgreSQL observability. At 19 stars and a 0.9% credibility score, it is still finding its footing, but the Rust foundation and focused feature set suggest good long-term stability. Install the pre-built binary and connect to your instance to evaluate it against your monitoring workflow. Do not expect the depth of pg_stat_statements queries or the integrations of mature tools, but as a quick diagnostic companion, it earns a spot in the toolbox.

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