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Cognee vs SuperLocalMemory: Pricing and Ratings Compared (2026)

Entry prices and free plans as read on each vendor's pricing page, and user ratings as published on review sites, for Cognee and SuperLocalMemory side by side. This page compares data; it is not a hands-on review.

On the data: On the data below, SuperLocalMemory leads on lower entry price. We do not name an overall winner for this pair.

Data comparison compiled by Toolradar, not hand-reviewed Methodology
Data comparison Pricing checked Oct 16, 2026

Short on time? Here's the quick answer

Based on published vendor pricing and features and on public review data, here's who should pick what:

Cognee

Build AI agents with persistent, structured graph memory

Best for you if:

  • • You want provides durable, shared memory for AI agents, improving their consistency and intelligence

SuperLocalMemory

Local, auditable memory for AI agents with layered, hybrid recall

Best for you if:

  • • You want runs locally, ensuring data privacy and no dependency on external APIs
At a glance: Cognee vs SuperLocalMemory
At a Glance
Cognee Cognee
SuperLocalMemory SuperLocalMemory
Starts at
Free plan, paid from $35/mo, billed monthly Developer plan
Free plan, paid from $4/user/mo, billed monthly Team plan
Category
AI Agents Data & Databases
AI Agents Developer Tools
Rating
n/a n/a
Free plan
Yes Yes

Choose Cognee or SuperLocalMemory?

Cognee

Choose Cognee if

  • You want provides durable, shared memory for AI agents, improving their consistency and intelligence
  • You want supports a wide range of data sources and agent frameworks, offering flexibility
SuperLocalMemory

Choose SuperLocalMemory if

  • You want runs locally, ensuring data privacy and no dependency on external APIs
  • You want governed memory with audit trails and compliance controls suitable for teams
  • Budget matters ($4/user/mo, billed monthly vs $35/mo, billed monthly)

In-Depth Analysis

Cognee Cognee

Build AI agents with persistent, structured graph memory

Good value

Cognee's pricing is fair, offering a generous Free tier for basic experimentation.

Strengths

  • Pro: Provides durable, shared memory for AI agents, improving their consistency and intelligence.
  • Pro: Supports a wide range of data sources and agent frameworks, offering flexibility.
  • Pro: Offers both open-source local development and scalable cloud/on-premise deployment options.
  • Pro: Automatically generates and updates ontologies, keeping knowledge structures fresh.
  • Pro: Ensures data security and compliance with options for private cloud or on-premise deployment.

Weaknesses

  • Con: Requires integration and configuration with existing agent systems.
  • Con: The complexity of graph memory and ontology management may have a learning curve for new users.
  • Con: Scalability and advanced features are primarily available in paid tiers.

Key features

Context Capture from diverse sources (files, databases, APIs, chat logs) Automated Parsing, Chunking, and Embedding Provenance Tracking for all ingested data Graph Memory Modeling (entities, relationships, ontologies) Recall Tuning and Permissions Control Compatibility with leading agent frameworks (e.g., LangGraph, OpenClaw)

SuperLocalMemory SuperLocalMemory

Local, auditable memory for AI agents with layered, hybrid recall

Good value

The Free tier is generous for small projects, and the Team tier at $4/user/month is very affordable for startups.

Strengths

  • Pro: Runs locally, ensuring data privacy and no dependency on external APIs
  • Pro: Governed memory with audit trails and compliance controls suitable for teams
  • Pro: Supports multiple agents, documents, images, and time-travel queries in one system

Weaknesses

  • Con: On-device answer check (Laya) requires Apple Silicon; Windows/Linux users need online Jev with a key
  • Con: Document indexing requires 16 GB RAM and is off by default

Key features

Three-tier recall: supported answer, closest memories, or 'not in memory' Layered recall with token budget and expandable depth Hybrid retrieval: semantic, BM25, entity-graph, temporal, associative, and picture channels On-device answer checking via Laya (Apple Silicon) or online Jev (optional) Governance: RBAC, audit trail, GDPR export/erasure, per-workspace isolation

Plans and prices: Cognee vs SuperLocalMemory

Plans and prices of Cognee and SuperLocalMemory, as read on each vendor's pricing page. Each plan keeps its own billing unit.
Tool Plans and prices Source
Cognee
  • Free: Free
  • Developer: $35/mo, billed monthly
  • Cloud (Team): $200/user/mo, billed monthly
  • On-Prem (Enterprise): Custom pricing
cognee.ai/pricing read Oct 16, 2026
SuperLocalMemory
  • Free: Free
  • Team: $4/user/mo, billed monthly
  • Enterprise: Custom pricing
github.com/pricing read Oct 16, 2026

Prices as read on each vendor's own pricing page on the date shown. Plans are listed per tool and are not matched against the other tool's plans: a plan name or price in one column says nothing about the same row in the other. Details on Cognee pricing and SuperLocalMemory pricing.

Key Takeaways

Cognee

  • Choose if you want build AI agents with persistent, structured graph memory

SuperLocalMemory

  • Lower entry price: $4/user/mo, billed monthly vs $35/mo, billed monthly

What the data shows

On the data below, SuperLocalMemory leads on lower entry price. We do not name an overall winner for this pair.

  • SuperLocalMemory has the lower entry price: $4/user/mo, billed monthly (Team) against $35/mo, billed monthly (Developer) for Cognee.
  • Both have a free plan.

Criteria: user rating (only above 20 reviews on both sides, gap of 0.2 or more), entry price (only on the same billing basis), free plan. How we rate

Frequently Asked Questions

How do Cognee and SuperLocalMemory compare in 2026?

On the data below, SuperLocalMemory leads on lower entry price. We do not name an overall winner for this pair. SuperLocalMemory has the lower entry price: $4/user/mo, billed monthly (Team) against $35/mo, billed monthly (Developer) for Cognee. Both have a free plan.

What are Cognee and SuperLocalMemory used for?

Cognee: Build AI agents with persistent, structured graph memory. SuperLocalMemory: Local, auditable memory for AI agents with layered, hybrid recall.

What does Cognee cost vs SuperLocalMemory?

Cognee's cheapest paid plan is Developer at $35/mo, billed monthly; it also has a free plan. SuperLocalMemory's cheapest paid plan is Team at $4/user/mo, billed monthly; it also has a free plan. Prices read on the vendors' pricing pages, latest check Oct 16, 2026.

What's the main difference between Cognee and SuperLocalMemory?

Cognee's main strength: provides durable, shared memory for AI agents, improving their consistency and intelligence. SuperLocalMemory's main strength: runs locally, ensuring data privacy and no dependency on external APIs.

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