Build & scale AI apps 10x faster with Surreal Cloud. 🚀 29,000+ developers already on board. 👉 Follow @SurrealDB for code-level hacks & fresh feature drops.

💜 Dev quote of the week. Some devs choose their database. Others find their soulmate. Vectors, graphs, docs and realtime sync, in one irresistible package. Careful, you might just catch feelings. Shoutout @autodidacc_fyi for the love!.🔗

Generating vector search embeddings in @LangChainAI? To optimise your accuracy and performance, it's important to compare different models. Read our embeddings quick start guide for examples. 👉 @ollama | @OpenAI | @MistralAI | Google Gemini |

GraphRAG leverages knowledge graphs, giving LLMs richer context for more accurate answers. @mithridates walks you through each step to build a GenAI chatbot in Rust with @LangChainAI, SurrealDB, and the langchain_rust crate. 👉

As LLMs and intelligent apps hit the edge, devices need an embedded database that’s lean, secure, fast, and rich-data savvy. Learn why our multi-model database, built in Rust, is a perfect fit for AI-powered workloads at the edge. 👉

Do you want to use SurrealQL syntax highlighting in your IDE? Community member Cellan Hall's tree-sitter grammar SurrealQL makes this easy to integrate, as shown in the @zeddotdev extension for SurrealDB. 🔗 

RT @CorleyAaliyah: Grok nailed my SurrealDB Max integration patterns, then suggested invading Poland. 🤷‍♀️. "would you like me to update th….

Need a database offering multi-model flexibility, predictable performance, and the ability to embed within your app? That’s why @CalamuProtect relies on ours across both cloud and on-premise environments. Learn more. 👉

Curious about how to combine graph-linked facts and vector embeddings to give LLM apps a persistent memory layer that unifies search with reasoning? Join our online session to learn more. 👉

Want to build a chatbot that understands context? 🤖 We break it down with a minimal @LangChainAI example. Learn how to use vector stores and graphs to generate intelligent, natural language answers. 👉

Did you know you can store @MistralAI embeddings as SurrealDB vectors via the Rust SDK for semantic search? Our own @mithridates shows you how in a step by step guide. 👉

Databases are at the core of traditional software apps. With the rise of Agentic AI, the role of databases must evolve to serve as the “Agentic Memory” at the heart of reliable agentic systems. @tobiemh explains. 👉

Want to trigger an event when specific data changes in our multi-model database? Use SurrealQL’s DEFINE EVENT statement to define custom logic on record creation. Learn more in our docs. 👉

Sunday Spotlight: our official @LangChainAI integration is live! 🦜🔗. • SurrealDBVectorStore.• SurrealDBGraph and SurrealDBGraphQAChain (experimental). pip install langchain-surrealdb and start building smarter RAG.

Engineers at NVIDIA, Tencent, and Samsung already trust SurrealDB. Now it’s your turn. One powerful database unifies vectors, graphs, docs, and time-series, scaling from edge to petabyte clusters so your AI apps ship faster. 🔗

Surreal Cloud’s network capabilities make it possible to send and receive HTTP requests natively in-database securely and conveniently. @Datastorydesign shows you how to enable this. Spin up an instance and try it. 👉

Want to simplify your AI pipelines? Our guide will enable you to scrap ETL and build pipelines that blend multi-model data and AI logic directly inside one ACID database. Learn more. 👉

Shout out to community member, Albert Marashi, for the @zeddotdev extension for SurrealQL, our database query language. It adds SurrealQL syntax highlighting right inside Zed. Learn more and download. 👉

There's no easier way to get started with @LangChainAI than with SurrealDB. In under 1 minute, you can store documents together with @ollama generated embeddings, and do a similarity search to retrieve them. Learn more. 👉

RT @steveliles: props to these guys, they are building innovative stuff at a mad pace (haven't used it, but reading the tips is an eye-open….

A schema defines your database’s structure and rules. Early definition ensures consistent data storage, linking, and behaviour throughout your project. Some tips from our own @mithridates show you how to design one that works for you. 👉