docs: ground the platform/OSS comparison and memory-type status in reality

This commit is contained in:
kartik-mem0
2026-08-11 21:13:23 +05:30
parent 35a125585e
commit f288a05d66
2 changed files with 113 additions and 125 deletions
+47 -56
View File
@@ -6,7 +6,7 @@ icon: "code-compare"
## Which Mem0 is right for you?
Mem0 offers two powerful ways to add memory to your AI applications. Choose based on your priorities:
Mem0 offers two ways to add memory to your AI applications. Both run the same core extraction and retrieval logic; the Platform adds hosting, a small set of v3-only capabilities, and management surfaces that OSS does not have.
<CardGroup cols={2}>
<Card
@@ -16,7 +16,7 @@ Mem0 offers two powerful ways to add memory to your AI applications. Choose base
>
**Managed, hassle-free**
Get started in 5 minutes with our hosted solution. Perfect for fast iteration and production apps.
Get started in 5 minutes with our hosted solution. No vector store, LLM, or embedder to configure.
</Card>
<Card
@@ -32,89 +32,80 @@ Mem0 offers two powerful ways to add memory to your AI applications. Choose base
---
## Feature Comparison
## What's the same
The core memory loop is identical on both: `add`, `search`, `get`, `get_all`, `update`, `delete`, `delete_all`, and per-memory `history` all exist on the self-hosted `Memory`/`AsyncMemory` classes and on the hosted `MemoryClient`/`AsyncMemoryClient`. Both support:
- **Entity scoping** by `user_id`, `agent_id`, and `run_id`
- **Enhanced metadata filtering**: `eq`, `ne`, `gt`, `gte`, `lt`, `lte`, `in`, `nin`, `contains`, `icontains`, wildcards, and nested `AND`/`OR`/`NOT` logic
- **Entity-aware ranking**: both extract entities from memory text and use shared entities to boost related results at search time
- **Multimodal input**, **memory expiration** (`expiration_date`), **reranking**, **procedural memory** (Python), and **custom extraction instructions** (`custom_instructions`)
- Python and JavaScript SDKs, plus a REST API (self-hosted via `server/`, or hosted)
## What's actually different
<AccordionGroup>
<Accordion title="Setup & Getting Started" icon="rocket">
<Accordion title="Hosting & infrastructure" icon="server">
| Feature | Platform | Open Source |
|---------|----------|-------------|
| **Time to first memory** | 5 minutes | 15-30 minutes |
| **Infrastructure needed** | None | Vector DB + Python/Node env |
| **API key setup** | One environment variable | Configure LLM + embedder + vector DB |
| **Maintenance** | Fully managed by Mem0 | Self-managed |
| **Vector store, LLM, embedder** | Run and tuned by Mem0 | You provision, configure, and pay for each |
| **Scaling & availability** | Managed | Your responsibility |
| **Web dashboard** | `app.mem0.ai` | Not included |
| **Time to first memory** | Minutes (API key only) | Depends on your vector DB / LLM setup |
</Accordion>
<Accordion title="Core Memory Features" icon="brain">
<Accordion title="Entity scoping & workspace structure" icon="layer-group">
| Feature | Platform | Open Source |
|---------|----------|-------------|
| **User & agent memories** | ✅ | ✅ |
| **Smart deduplication** | ✅ | ✅ |
| **Semantic search** | ✅ | ✅ |
| **Memory updates** | ✅ | ✅ |
| **Multi-language SDKs** | Python, JavaScript | Python, JavaScript |
| **Scoping identifiers** | `user_id`, `agent_id`, `run_id`, plus `app_id` for app/tenant separation | `user_id`, `agent_id`, `run_id` only, no `app_id` |
| **Organizations & projects** | Multi-org, multi-project, with member roles ([API reference](/api-reference/organization/get-org)) | No org/project concept; a single local config |
| **Project-wide event feed** | `GET /v1/events/` lists recent add/search/delete events per org and project, usable for dashboards, alerting, or audit trails | Only per-memory `history(memory_id)`, no project-wide event log |
See [Entity-Scoped Memory](/platform/features/entity-scoped-memory) for the full `app_id` model.
</Accordion>
<Accordion title="Advanced Capabilities" icon="sparkles">
<Accordion title="Search-time ranking (v3-only)" icon="sparkles">
| Feature | Platform | Open Source |
|---------|----------|-------------|
| **Multimodal support** | ✅ | ✅ |
| **Custom categories** | ✅ | Limited |
| **Advanced retrieval** | ✅ | ✅ |
| **Temporal reasoning** | ✅ (v3) | ❌ |
| **Memory decay** | ✅ (v3) | ❌ |
| **Graph memory** | ✅ Built-in | ✅ External graph store |
| **Memory filters v2** | ✅ | ⚠️ (via metadata) |
| **Webhooks** | ✅ | ❌ |
| **Memory export** | ✅ | ❌ |
| **Graph Memory** | Native, always-on graph over extracted entities; connections feed directly into the ranking `score` ([details](/platform/features/graph-memory)) | Removed. OSS previously connected external graph stores (Neo4j, Memgraph, Kuzu, Apache AGE); that integration was dropped when the v3 pipeline landed. OSS still extracts entities and uses them to boost ranking, but there is no queryable graph and no `relations` field |
| **Memory Decay** | Opt-in per project; reinforces recently-used memories and gently dampens stale ones at search time ([details](/platform/features/memory-decay)) | Not supported. Passing `decay` raises `"The decay parameter is not supported by the OSS Memory SDK."` |
| **Temporal Reasoning** | Boosts memories whose event dates match the time expressed in a query (`timestamp` / `reference_date`) ([details](/platform/features/temporal-reasoning)) | Not supported. Both parameters raise a "not supported by the OSS Memory SDK" error |
| **Dream (background consolidation)** | Continuously synthesizes patterns, supersedes outdated facts, and merges duplicates per user ([details](/platform/features/dream)) | Not available |
</Accordion>
<Accordion title="Infrastructure & Scaling" icon="server">
<Accordion title="Configuration & data operations" icon="sliders">
| Feature | Platform | Open Source |
|---------|----------|-------------|
| **Hosting** | Managed by Mem0 | Self-hosted |
| **Auto-scaling** | ✅ | Manual |
| **High availability** | ✅ Built-in | DIY setup |
| **Vector DB choice** | Managed | 20+ stores: Qdrant, Pinecone, Chroma, Weaviate, Milvus, pgvector |
| **LLM choice** | Managed (optimized) | 15+ providers: OpenAI, Anthropic, Gemini, Groq, Ollama, Together |
| **Data residency** | US (expandable) | Your choice |
| **Custom categories** | Set per project or per `add` call ([details](/platform/features/custom-categories)) | Not supported. `Memory.add()` has no `custom_categories` parameter, and OSS project updates are rejected outright |
| **Webhooks** | Project-scoped HTTP callbacks on memory and ingest events ([details](/platform/features/webhooks)) | Not available |
| **Memory Export** | Schema-driven structured export jobs over filtered memories ([details](/platform/features/memory-export)) | Not available |
</Accordion>
<Accordion title="Pricing & Cost" icon="dollar-sign">
| Aspect | Platform | Open Source |
|--------|----------|-------------|
| **License** | Usage-based pricing | Apache 2.0 (free) |
| **Infrastructure costs** | Included in pricing | You pay for VectorDB + LLM + hosting |
| **Support** | Included | Community + GitHub |
| **Best for** | Fast iteration, production apps | Cost-sensitive, custom requirements |
</Accordion>
<Accordion title="Development & Integration" icon="code">
| Feature | Platform | Open Source |
<Accordion title="Support" icon="life-ring">
| Channel | Platform | Open Source |
|---------|----------|-------------|
| **REST API** | ✅ | ✅ (self-hosted server) |
| **Python SDK** | ✅ | ✅ |
| **JavaScript SDK** | ✅ | ✅ |
| **Framework integrations** | LangChain, CrewAI, LlamaIndex, and 20+ more | Same |
| **Dashboard** | ✅ Web-based | ❌ |
| **Analytics** | ✅ Built-in | DIY |
| **Community & maintainers** | Discord, GitHub Discussions, direct calls with the founders | Same: Discord, GitHub Discussions, direct calls with the founders |
Support channels are currently the same for both. If you need something contractual (a support SLA, for example), ask before assuming it exists: it is not documented as a Platform benefit today.
</Accordion>
</AccordionGroup>
User Profiles are not listed above. The feature is still being finalized internally, so this page does not present it as an available Platform benefit.
---
## Decision Guide
**Choose Platform if you want:**
- Fast time to market: get your AI app with memory live in hours, not weeks.
- Production-ready hosting: auto-scaling, high availability, and managed infrastructure.
- Built-in analytics: track memory usage, query patterns, and user engagement through the dashboard.
- Advanced features: webhooks, memory export, custom categories, and priority support.
- Zero infrastructure: no vector store, LLM, or embedder to provision or tune.
- The v3-only ranking features: Graph Memory, Memory Decay, Temporal Reasoning, and Dream.
- App-level and org/project-level scoping, plus webhooks, memory export, and custom categories.
**Choose Open Source if you need:**
- Full data control: host everything on your infrastructure with complete data residency.
- Custom configuration: choose your own vector DB, LLM provider, embedder, and deployment strategy.
- Extensibility: modify the codebase, add custom features, and contribute back to the community.
- Cost optimization: use local LLMs (Ollama), self-hosted vector DBs, and optimize for your use case.
- Full data control: host everything on your own infrastructure.
- Custom configuration: your own vector DB, LLM provider, and embedder ([25 vector stores](/components/vectordbs/overview), [18 LLM providers](/components/llms/overview), [11 embedders](/components/embedders/overview) at the time of writing).
- Extensibility: modify the codebase, add custom providers, and contribute back.
- Cost optimization: local LLMs (Ollama), self-hosted vector DBs, no usage-based billing.
---