Software Alternatives, Accelerators & Startups

Sheety VS Agentmemory

Compare Sheety VS Agentmemory and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Sheety logo Sheety

Turn any Google sheet into an API instantly, for free. Power websites, apps, or whatever you like, all from a spreadsheet. Changes to your spreadsheet update your API in realtime. Neat

Agentmemory logo Agentmemory

Persistent memory for Claude Code, Codex & coding agents
  • Sheety Landing page
    Landing page //
    2021-09-26
Not present

Sheety features and specs

  • Easy integration
    Sheety offers simple and straightforward APIs that allow users to convert Google Sheets into RESTful APIs, facilitating quick integration into various applications.
  • Cost-effective
    Sheety provides a free tier with essential features, making it a cost-effective solution for small projects or startups with limited budgets.
  • No-code solution
    Sheety allows non-developers to connect their Google Sheets data to other apps without requiring any coding knowledge.
  • Automation capabilities
    Users can automate workflows by integrating Sheety with other tools like Zapier, improving productivity and reducing manual tasks.
  • Real-time updates
    Changes in the Google Sheets are reflected almost instantly in the API endpoints, ensuring data is always up-to-date.

Possible disadvantages of Sheety

  • Limited scalability
    For larger projects with complex needs, Sheetyโ€™s features may not be sufficient, requiring users to invest in more robust data management solutions.
  • Privacy concerns
    Sharing sensitive information via Sheety's API can be risky if proper authentication and data security measures are not in place.
  • Dependency on Google Sheets
    Sheety relies heavily on Google Sheets, so any limitations or downtime of Google Sheets directly impacts the functionality of Sheety.
  • API rate limits
    The service may have API rate limits that could restrict high-frequency data updates or extensive CRUD operations, posing challenges for data-intensive applications.

Agentmemory features and specs

  • Simple API
    Agentmemory provides a straightforward and minimal API for creating, searching, updating, and deleting memories, making it easy for developers to integrate memory capabilities into AI agents without dealing with complex configurations.
  • Built on ChromaDB
    It leverages ChromaDB as its underlying vector database, providing reliable semantic search and embedding capabilities out of the box without requiring developers to set up separate infrastructure.
  • Lightweight and Easy to Install
    Agentmemory is a lightweight Python package that can be installed via pip with minimal dependencies, making it quick to get started with and easy to incorporate into existing projects.
  • Category-Based Memory Organization
    Memories can be organized into categories (topics), allowing agents to store and retrieve information in a structured way, which helps with context management and retrieval accuracy.
  • No Server Required
    Agentmemory can run entirely locally without needing a separate server or cloud service, making it suitable for development, prototyping, and privacy-sensitive applications where data should stay on the local machine.

Possible disadvantages of Agentmemory

  • Limited Ecosystem and Community
    Agentmemory is a relatively niche and small project with a limited community compared to more established memory and vector database solutions, which means fewer resources, tutorials, and community support are available.
  • Basic Feature Set
    While simplicity is a strength, the library may lack advanced features such as sophisticated memory consolidation, decay mechanisms, importance scoring, or complex querying capabilities that more mature memory frameworks offer.
  • Tight Coupling to ChromaDB
    Being built specifically on ChromaDB means developers are locked into that particular vector store and cannot easily swap it out for alternatives like Pinecone, Weaviate, or FAISS without significant refactoring.
  • Limited Scalability
    As a locally-run, lightweight solution, Agentmemory may not scale well for production applications that require handling large volumes of memories, high concurrency, or distributed deployments.
  • Sparse Documentation and Examples
    The project's documentation, while covering the basics, may lack comprehensive examples, best practices, and advanced usage patterns that developers need when building complex agent-based systems.

Analysis of Sheety

Overall verdict

  • Sheety is considered good for simplifying the process of using spreadsheets as a backend service. Its ease of use, especially for those unfamiliar with traditional development environments, makes it a practical solution for specific use cases.

Why this product is good

  • Sheety is a useful tool for those looking to turn their Google Sheets into a simple RESTful API. It offers a straightforward way to integrate spreadsheets with other applications, making it a good choice for prototyping, small projects, or integrating data without handling complex backend setups.

Recommended for

  • Non-developers looking for an easy way to create a backend for their applications.
  • Developers who need to quickly prototype applications with spreadsheet data.
  • Small teams or startups who want to leverage existing Google Sheets data without setting up a complex database.

Analysis of Agentmemory

Overall verdict

  • AgentMemory (agent-memory.dev) appears to be a solid, purpose-built solution for developers who need persistent memory management in AI agent applications, offering a focused feature set for storing, retrieving, and managing contextual data across agent sessions.

Why this product is good

  • Provides dedicated memory persistence for AI agents, enabling context retention across sessions and conversations
  • Designed specifically for the agentic AI use case, which can simplify development compared to building custom memory layers
  • Likely offers developer-friendly APIs and SDKs to integrate memory capabilities quickly
  • Can improve agent performance by allowing recall of past interactions, user preferences, and long-term context
  • Reduces boilerplate work for teams building conversational or autonomous AI systems

Recommended for

  • Developers building AI agents or LLM-powered applications that require long-term memory
  • Teams creating conversational assistants that need to remember user context across sessions
  • Startups and companies prototyping autonomous or multi-step agent workflows
  • Engineers seeking a managed memory layer instead of building persistence infrastructure from scratch
  • Projects involving personalized AI experiences that depend on retained user data and history

Sheety videos

Arundhati Climax Scene REACTION | Anushka Sheety, Sonu Sood | Parbrahm&Anurag

More videos:

  • Review - Yash Sister Deepikadas Mother Speech About Shine Sheety in Bigboss7 | Deepika Das ShineShetty
  • Review - SINGHAM 3 CONFIRM AFTER SOORYAVANSHI/AJAY DEVGAN,AKSHAY KUMAR,ROHIT SHEETY/SINGHAM 3/REVIEW BROTHERS

Agentmemory videos

No Agentmemory videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Sheety and Agentmemory)
API Tools
100 100%
0% 0
Developer Tools
0 0%
100% 100
Spreadsheets
100 100%
0% 0
AI
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Sheety seems to be more popular. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Sheety mentions (11)

  • Using Google Sheets as the back end/APIs of your app
    Neat! This seems very similar to Sheety[0], which I've used a bunch of times before (and found a few bugs...). Do you have any plans to open source? [0]https://sheety.co. - Source: Hacker News / over 2 years ago
  • Alternatives to Sparklite?
    You can just use retool alone or if you still want to use bubble maybe the easiest way would be to use https://sheety.co. Source: over 3 years ago
  • My mom have a little business and she do all on an excel, is there any way to create her a web page directly connected to a google sheets?
    Well thereโ€™s https://sheety.co that provides an api to write to google sheets. You just need to set up the fetch mechanism on your web page. Source: over 3 years ago
  • Shortcut to return data from specific Numbers cell
    Https://sheety.co/ I found this website, where I can have the API with the needed google sheet and with the API request/response, I am getting the required details. Source: over 3 years ago
  • Making an app that connects to Google Sheets
    Calling a 3rd party API: There is a complete ecosystem providing "google-sheets-as-DB". I personally tested and recommend https://sheetson.com/ but there are a lot more with free tiers https://sheetsu.com/ https://sheety.co/. Source: about 4 years ago
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Agentmemory mentions (0)

We have not tracked any mentions of Agentmemory yet. Tracking of Agentmemory recommendations started around Jun 2026.

What are some alternatives?

When comparing Sheety and Agentmemory, you can also consider the following products

Sheetsu - Turn Google Spreadsheet into API

Pieces for Developers - Centralized code snippet manager to streamline your workflow

Sheet 2 Site - Generate a website from ๐Ÿ“— Google Sheets

ChainMemory - Portable, verifiable memory for AI agents โ€” works across ChatGPT, Claude, Gemini and any MCP client

SheetBest - Turn a Google SpreadSheet into a JSON Database API

OpenMemory MCP - Your private, local memory layer for all AI tools