head to head · open source
llama_index vs paradedb
llama_index has 52,779 GitHub stars, 8,500 forks, 770 open issues and last shipped 8 days ago. paradedb has 9,473 stars, 496 forks, 193 open issues and last shipped yesterday. llama_index leads on adoption by 457% (52,779 vs 9,473 stars). llama_index is written in Python under MIT; paradedb is written in Rust under AGPL-3.0. llama_index has attracted 16% as many forks as stars, paradedb 5%. paradedb was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| llama_index | paradedb | |
|---|---|---|
| GitHub stars | ★ 53K | ★ 9.5K |
| License | MIT | AGPL-3.0 |
| Written in | Python | Rust |
| Last push | 2026-10-26 | 2026-11-02 |
| Forks | ⑂ 8.5K | ⑂ 496 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 53K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick paradedb if
- You want the paradedb feature set and don't need the biggest community
- You prefer the AGPL-3.0 license terms
- Your stack matches Rust
- You evaluated both and paradedb fits your workflow better
About llama_index
🗂️ LlamaIndex (OSS Framework) 🦙 [!NOTE] The current focus of LlamaIndex is to build the best AI powered engine for document parsing and extraction. LlamaParse is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. LiteParse represents our efforts to build the best free, fast, cheap text parser in the market. ParseBench and ExtractBench represent our commitment towards open benchmarking for parsing and extraction. The company itself has undergone an evolution since when this OSS framework first launched 3 years ago in 2023. Since the early days, the framework has consisted of a…
read the full llama_index overview →
About paradedb
Search without a second system. One Postgres for your application data, full text search, vector retrieval, and aggregations. Website • Docs • Community • Blog • Changelog Installation To install ParadeDB locally in a fresh Docker container and drop straight into a psql session: When you're ready to deploy, check out our hosting options. What is ParadeDB? ParadeDB upgrades Postgres with a custom index for fast full text and vector search, BM25 scoring, filtering, and aggregations. Your application data and search engine live in one database, with no second system to deploy and nothing to…
read the full paradedb overview →
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Frequently asked questions
Is llama_index or paradedb more popular?
llama_index has 52,779 GitHub stars and paradedb has 9,473. llama_index has the larger community by that measure.
Are llama_index and paradedb free?
Both are open source. llama_index is licensed under MIT and paradedb under AGPL-3.0. Neither carries a licence fee.
What is the difference between llama_index and paradedb?
llama_index is written in Python and paradedb in Rust. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, llama_index or paradedb?
Choose llama_index if you want the larger community (52,779 stars) or its MIT licence terms. Choose paradedb if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.