---
title: "magnitude vs redis"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/plasticityai-magnitude-vs-redis-redis"
tools: ["plasticityai-magnitude", "redis-redis"]
---

# magnitude vs redis

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick magnitude if magnitude is a Python library for handling vector embeddings efficiently and quickly. It integrates with several popular embedding methods; pick redis if redis is an in-memory database designed as a versatile cache and data structure store with advanced features such as JSON operations and vector searches, making it suitable for real-time applications.

[magnitude](https://github.com/plasticityai/magnitude) reports 1.7k GitHub stars, 122 forks, and 41 open issues, last pushed Aug 3, 2023. [redis](http://redis.io) has 75k stars, 25k forks, and 2.9k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [magnitude's repository](https://github.com/plasticityai/magnitude) and [redis's repository](https://github.com/redis/redis).

| | [magnitude](/tools/plasticityai-magnitude.md) | [redis](/tools/redis-redis.md) |
| --- | --- | --- |
| Tagline | A fast, efficient universal vector embedding utility package. | Redis is a preferred cache, data structure server, and document & vector query engine for real-time applications. |
| Stars | 1,664 | 75,394 |
| Forks | 122 | 24,718 |
| Open issues | 41 | 2,867 |
| Language | Python | C |
| Adopt for | Magnitude is a Python library for handling vector embeddings efficiently and quickly. It integrates with several popular embedding methods. | Redis is an in-memory database designed as a versatile cache and data structure store with advanced features such as JSON operations and vector searches, making it suitable for real-time applications. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | Other |
| Categories | Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [magnitude](/tools/plasticityai-magnitude.md) | [redis](/tools/redis-redis.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Very active (96%) |
| Days since push | 1073d | 0d |
| Open issues (now) | 41 | 2.9k |
| Full report | [trust report](/tools/plasticityai-magnitude/trust.md) | [trust report](/tools/redis-redis/trust.md) |

## Decision facts: magnitude

- **Adopt for:** Magnitude is a Python library for handling vector embeddings efficiently and quickly. It integrates with several popular embedding methods.

## Decision facts: redis

- **Adopt for:** Redis is an in-memory database designed as a versatile cache and data structure store with advanced features such as JSON operations and vector searches, making it suitable for real-time applications.

## Choose when

### Choose magnitude if…

- magnitude is primarily Python; redis is C.
- License: magnitude is MIT, redis is Other.
- Tags unique to magnitude: embeddings, fasttext, gensim, glove.
- - When you need to perform memory-efficient operations on vector embeddings, including those from FastText or Word2Vec.

### Choose redis if…

- redis is primarily C; magnitude is Python.
- License: redis is Other, magnitude is MIT.
- Tags unique to redis: cache, caching, database, in-memory.
- You need high-speed access to frequently used data due to Redis's in-memory nature.

## When NOT to use magnitude

- - If your project involves non-Python ecosystems, as Magnitude is strictly a Python library and thus not compatible with other programming environments.
- - When the primary focus of your work does not include handling large vector embeddings or specific operations that benefit from memory efficiency provided by Magnitude.

## When NOT to use redis

- Your project has limited memory resources since Redis relies on in-memory storage, which could lead to high costs or operational challenges with large datasets.
- You prioritize persistence over speed; while Redis offers persistence options, its primary design is for real-time access and not robust disk-based backup solutions like traditional SQL databases.
- Your application workload does not benefit from the fast read/write capabilities and rich data structure support offered by Redis, possibly implying that a less specialized database would suffice.

## Common questions

### What is the difference between magnitude and redis?

magnitude: A fast, efficient universal vector embedding utility package.. redis: Redis is a preferred cache, data structure server, and document & vector query engine for real-time applications.. See the comparison table for live GitHub stats and shared categories.

### When should I choose magnitude over redis?

Choose magnitude over redis when magnitude is primarily Python; redis is C; License: magnitude is MIT, redis is Other; Tags unique to magnitude: embeddings, fasttext, gensim, glove; - When you need to perform memory-efficient operations on vector embeddings, including those from FastText or Word2Vec.

### When should I choose redis over magnitude?

Choose redis over magnitude when redis is primarily C; magnitude is Python; License: redis is Other, magnitude is MIT; Tags unique to redis: cache, caching, database, in-memory; You need high-speed access to frequently used data due to Redis's in-memory nature.

### When should I avoid magnitude?

- If your project involves non-Python ecosystems, as Magnitude is strictly a Python library and thus not compatible with other programming environments. - When the primary focus of your work does not include handling large vector embeddings or specific operations that benefit from memory efficiency provided by Magnitude.

### When should I avoid redis?

Your project has limited memory resources since Redis relies on in-memory storage, which could lead to high costs or operational challenges with large datasets. You prioritize persistence over speed; while Redis offers persistence options, its primary design is for real-time access and not robust disk-based backup solutions like traditional SQL databases. Your application workload does not benefit from the fast read/write capabilities and rich data structure support offered by Redis, possibly implying that a less specialized database would suffice.

### Is magnitude or redis more popular on GitHub?

redis has more GitHub stars (75,394 vs 1,664). Stars measure visibility, not whether either tool fits your constraints.

### Are magnitude and redis open source?

Yes - both are open-source projects on GitHub (magnitude: MIT, redis: Other).

### Where can I find alternatives to magnitude or redis?

GraphCanon lists graph-backed alternatives at [magnitude alternatives](/tools/plasticityai-magnitude/alternatives) and [redis alternatives](/tools/redis-redis/alternatives) ([magnitude markdown twin](/tools/plasticityai-magnitude/alternatives.md), [redis markdown twin](/tools/redis-redis/alternatives.md)), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at [this comparison](/compare/plasticityai-magnitude-vs-redis-redis.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, magnitude or redis?

magnitude: Dormant. redis: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for magnitude and redis?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [magnitude trust report](/tools/plasticityai-magnitude/trust); [redis trust report](/tools/redis-redis/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=plasticityai-magnitude`](/api/graphcanon/graph?tool=plasticityai-magnitude)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_