AI · alternatives · 2026
24 alternatives to LLM Memory Storage that scales, easily integrates, and is smart
I built a super easy to integrate memory storage and retrieval system for NodeJS projects because I saw a need for information to be shared and persisted across LLM chat sessions (and many other LLM feature interactions). I tried to keep the barrier to use as low as possible so I included built-in support for major LLMs (GPT, Gemini, and Claude) as well as major vector store providers (Weaviate and Pinecone). The memory store works by ingesting and automatically extracting “memories” (summarized single bits of information) from LLM interactions and vectorizing those. When you want to provide…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
Built this for my LLM workflows - needed searchable, persistent memory that wouldn't blow up storage costs. I also wanted to use it locally for my research. It's a content-addressed storage system with block-level deduplication (saves 30-40% on typical codebases). I have integrated the CLI tool into most of my workflows in Zed, Claude Code, and Cursor, and I provide the prompt I'm currently using in the repo. The project is in C++ and the build system is rough around the edges but is tested on macOS and Ubuntu 24.04.
2025 · github.com · its alternatives →
- 2
I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…
2025 · github.com · its alternatives →
- 3
Hey HN! I built a proof-of-concept for AI memory using Git instead of vector databases. The insight: Git already solved versioned document management. Why are we building complex vector stores when we could just use markdown files with Git's built-in diff/blame/history? How it works: Memories stored as markdown files in a Git repo Each conversation = one commit git diff shows how understanding evolves over time BM25 for search (no embeddings needed) LLMs generate search queries from conversation context Example: Ask "how has my project evolved?" and it uses git diff to show actual…
2025 · github.com · its alternatives →
- 4
Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc. - CaviraOSS/LongMemory
Dec 2025 · github.com · its alternatives →
- 5
Shared persistent memory across all your LLMs.
2025 · teamlayer.xyz · its alternatives →
- 6
Rememberall▲201Open source solution for long term memory for LLMs
2024 · github.com · its alternatives →
- 7
- 8ZL
Zep is a long-term memory store designed for conversational AI applications built using modern LLMs. It handles the storage, summarization, embedding, indexing, and enrichment of chat histories, and offers developers a simple, low-latency API to this data. Chat history storage is an infrastructure challenge all developers and enterprises face as they look to move from prototypes to deploying conversational AI applications that provide rich and intimate experiences to users. Key features include long-term memory persistence, auto-summarization, vector search, auto-token counting, and Python…
2023 · its alternatives →
- 9
AI memory tool that lives where you work
Jan 2026 · chromewebstore.google.com · its alternatives →
- 10
One memory across OpenClaw, ChatGPT, Claude & Gemini
Feb 2026 · maximem.ai · its alternatives →
- 11RG
Hey HN! I'm José, and I built Recall to solve a problem that was driving me crazy. The Problem: I use Claude for coding daily, but every conversation starts from scratch. I'd explain my architecture, coding standards, past decisions... then hit the context limit and lose everything. Next session? Start over. The Solution: Recall is an MCP (Model Context Protocol) server that gives Claude persistent memory using Redis + semantic search. Think of it as long-term memory that survives context limits and session restarts. How it works: - Claude stores important context as "memories" during…
2025 · npmjs.com · its alternatives →
- 12
Captures and stores your chat from various AI platforms
Mar 2026 · ai-memory-beta.vercel.app · its alternatives →
- 13
OpenMemory Chrome Extension: Long-term memory for ChatGPT, Claude, Perplexity, Grok etc - mem0ai/mem0-chrome-extension
2024 · github.com · its alternatives →
- 14
DeltaMemory▲104Most AI agents forget everything between sessions. We built DeltaMemory to fix that. It's a cognitive memory layer that gives agents persistent recall, automatic fact extraction, and temporal reasoning — via a single SDK call. Key numbers: - 89% accuracy on LoCoMo long-term conversation benchmark - 50ms p50 retrieval latency - 97% cost reduction vs raw token re-processing Open source SDKs, works with any LLM stack. Currently in early access. Happy to answer questions about the architecture, benchmark methodology, or how we handle knowledge graphs.
Feb 2026 · deltamemory.com · its alternatives →
- 15
Tell MemorySync a fact, reload the page, then ask for it back in your own words. No signup. Every API call shown in cURL, Python and Node.js.
10d ago · memorysync.io · its alternatives →
- 16
I’d like to use LLMs for remembering all kinds of things: fitness, to-do lists, contacts, bug reports, research links, whatever. But there is no way to do that now. For example, if I find a great coding tutorial in chat, or tell it how much I ran yesterday, it forgets that when I close the chat. Even if I keep the chat history, I still need to scour through lots of messages to find the data I want. Ideally, Claude would remember all this, and I’d be able to find it later with ease. This is what my team built. It is a collaborative database you add to any LLM that supports MCP. (Claude Code,…
2025 · dry.ai · its alternatives →
- 17
Local-first AI memory layer for any LLM. Persistent knowledge graph, entity extraction, semantic retrieval. Works with Ollama, OpenAI, Anthropic, or any OpenAI-compatible backend. - zaydmulani09/mnemo
Jun 2026 · github.com · its alternatives →
- 18
Semantic search alone is not enough to capture all connected facts, they will capture the semantically most identical memory only. Tested on HotpotQA public dataset: Vector + BM25 + entity graph: BothFound@5 71.5% Vector + BM25 only: BothFound@5 59.5% Entity graph is the game changer to extract connected facts. More Benchmark result: LongMemEval-S: 84.8% recallAll@5 LoCoMo-10: 59% vs zep cloud 28% What is your approach for connected facts retrieval ?
Jul 2026 · yourmemoryai.xyz · its alternatives →
- 19
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
- 20
Hey HN - we launched Zep's document vector DB today. Zep is an open source memory store for LLM apps, and this builds on existing chat history memory persistence, embedding, and enrichment capabilities. Zep uses Postgres and pgvector for database operations and vector search. Vector search can be complicated on Postgres, with careful configuration required at both index creation and query time. We've focused on significantly improving this developer experience. Zep automatically selects index and query parameters for developers based on best practices and known heuristics. Vector database…
2023 · github.com · its alternatives →
- 21
- 22
Memory Sync▲13Take your AI memory with you across Claude, Gemini, and more
Apr 2026 · mem-sync.kareverie.com · its alternatives →
- 23RC
Hello HN! We're building a caching solution for LLMs (ChatGPT, Claude). By combining cutting-edge approaches, such as edge computing, prompt compression, vectorization, and others - it can reduce your AI bills by up to 10x and significantly lower response times. Key Features: - cost efficiency: our system stores frequent queries, reducing the number of upstream (paid) API calls - fast responses: with various nodes globally, we reduce latency by serving data from the nearest location - scalability: designed to handle increasing loads and data sizes without degrading performance. The cache…
2024 · edgematic.dev · its alternatives →
- 24
myNeutron▲26Portable memory that follows you across AI chats.
2025 · myneutron.ai · its alternatives →
Also compare
- Yet another memory system for LLMs alternatives
- Core – open source memory graph for LLMs – shareable, user owned alternatives
- I replaced vector databases with Git for AI memory (PoC) alternatives
- A local-first memory store for LLM agents (SQLite) alternatives
- AI Memory Layer for ChatGPT and Claude. alternatives
- Rememberall alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →