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TmpState.dev
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TmpState.dev's answer:
TmpState is a tokenless temporary JSON database. One curl tmpstate.dev creates a real database and returns its URL - and that URL is the only credential. No signup, no API keys, no .env, no OAuth.
TmpState.dev's answer:
Compared to jsonbin.io, npoint.io, json-server, or standing up Firebase/Supabase, TmpState removes the entire setup step:
Best for throwaway and prototype state. It is honest about when not to use it: it is not meant to be your permanent production database.
TmpState.dev's answer:
Developers and the AI agents working on their behalf. Primarily:
TmpState.dev's answer:
TmpState came out of a recurring frustration in agent workflows: AI agents constantly need somewhere to keep state, but you cannot hand them your real cloud credentials, and wiring up a database mid-task kills the flow. So the model was inverted - build a database where the URL itself is the only credential, so an agent (or a person with one curl) can create its own backend instantly, with nothing to sign up for and nothing to leak. It is a solo, founder-built, agent-first product, launched in July 2026.
Based on our record, neo4j seems to be more popular. It has been mentiond 36 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.
The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools for your Claude Code instance to manage long-term memory operations, and your memories data never leaves your machine. - Source: dev.to / 5 months ago
Perhaps the biggest promoter of the term has been Philip Rathle from Neo4j, which offers the best-known graph database system for storing knowledge graphs. But here's where the confusion starts: Is a knowledge graph something you store, or is it how you store something? It's not just a knowledge graphโit's also a graph database. That distinction matters, but the boundaries are blurry. - Source: dev.to / 6 months ago
The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are Neptune from Amazon and Neo4j. In a case where you need a solution that can accommodate both vector and graph, Weaviate fits the bill. - Source: dev.to / about 1 year ago
Neo4j is a leading graph database that is easy to use and powerful for knowledge graphs. - Source: dev.to / about 1 year ago
Neo4j is one of the most popular graph databases. It offers powerful querying capabilities through its Cypher query language. - Source: dev.to / over 1 year ago
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Supabase - An open source Firebase alternative
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Upstash - Upstash provides Serverless Redis and Kafka as a service.
OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.
Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.