#10
B
Rank #217
Flowise
A drag-and-drop visual builder for LangChain-style LLM workflows. Standout trait is rapid prototyping of agent/RAG pipelines, at the cost of production-grade data and security hardening.
58.0
/ 100
⚙ Full Stack
Node.js/Express backend running LangChain.js flow execution, React frontend for the flow canvas, SQLite by default (Postgres/MySQL optional) for flow and credential storage.
📈 Scaling Analysis
SQLite default and in-memory flow execution state make single-instance the common deployment; horizontal scaling requires externalizing both the DB and the credential store, and long-running flow executions can tie up a worker, limiting throughput per pod.
🚀 Running on Nexlayer
Single flowise pod with a postgres pod (postgres.pod:5432) to replace the SQLite default before going multi-replica; credentials are encrypted at rest but the encryption key must be set via env var, not baked into the image. Official image is Docker Hub namespaced — mirror via mirror.gcr.io.