EdgeBase
Beta

The EdgeBase Vision

Future-Ready Fully Managed Backend Platform

Edge-Native
Speed, reliability, no cold starts
Unified DX
No glue code or duct tape
Optional AI Stack
Memory, tools, gateway built-in

Why EdgeBase Exists

Core Insight

Frontend engineers want to build production-grade apps—fast—without dealing with fragmented backend infrastructure, poor observability, or edge-incompatible platforms. But today's backend options are either too generic or too AI-specific, lacking balance and modern design.

Too Many Services

Multiple services stitched manually — high cognitive load, messy integration, and complex setup.

Latency Issues

Cold starts, regional lag — bad UX, especially for global users.

No Real Memory Model

No persistent state per user/session — requires hacks via Redis or local state.

Poor Observability

No tracing, failure, or cost visibility — difficult to debug or optimize.

CORE PLATFORM FEATURES

The Platform

Auth

Email, OAuth, JWT out-of-the-box

PostgreSQL

Global-ready SQL via Hyperdrive or native connection

File Storage

R2-backed object storage with zero egress costs

Functions

Global compute via Workers, zero cold starts

Memory

Per-user/session scoped durable memory via Durable Objects

Knowledge Store

Built-in document ingestion, embedding, querying

Tool Binding

One config to expose HTTP, DB, or external workflows

Observability

Tracing, cost, usage, failure introspection

Developer Experience

Designed for modern product engineers, not backend specialists.

Interfaces

  • JS/TS SDK (@edgebase/client) – Works in browser, Node.js, and edge
  • CLIedgebase init, edgebase dev, edgebase deploy, edgebase trace
  • Dashboard – Logs, memory browser, usage metrics, deployment view
  • Config-as-Code – YAML or edgebase.config.ts

DX Principles

  • No boilerplate: Instant setup, zero fetch plumbing
  • CLI-first: Local dev, mock sessions, tracing built-in
  • Edge-native: Built for latency-sensitive apps
  • Fully Managed: No Docker, no cluster config, no glue code
ARCHITECTURE

Architecture Overview

Compute

Workers

Low-latency global execution

State

Durable Objects

Session-aware memory, coordination

Storage

R2

Secure object storage

Database

Postgres

Via Hyperdrive or BYODB

Use Cases

1. Fullstack SaaS Backend

Auth, DB, storage, file handling, user sessions. No cloud provider setup required, deploy from CLI.

2. Real-Time or Edge Apps

Global latency guarantees (<60ms). Durable state per user/session.

3. AI-Enhanced Products

Tools, memory, observability + gateway support. Declarative config, no additional frameworks required.

What We're Not

Not ML-ops tooling — We're focused on backend infrastructure, not ML model training or deployment pipelines.

Not CRUD-only — While we support CRUD out-of-box, we're built for complex, real-time, edge-native applications.

Not glued-together infra — Everything is unified, not a collection of services you need to wire together.

Not opinionated about frontend — Works with any frontend stack, framework, or platform.

We're the future-ready backend, engineered for modern product teams.

STRATEGIC POSITIONING

Strategic Positioning

EdgeBase is a fully managed backend for modern apps — fast to build, scalable by design, and built on edge-native primitives. It replaces 5+ tools and lets you ship faster, debug easier, and scale cheaper.

Edge-native

Speed, reliability, no cold starts

Modern dev ergonomics

SDK + CLI + dashboard

Optional AI stack

Memory, tools, gateway, observability

Unified DX

Fullstack without glue code or duct tape

Roadmap Concepts

Immediate

  • Core SDK (auth, memory, tools)
  • CLI + config setup
  • Postgres & R2 integration
  • Edge-native deploy flow

Mid-Term

  • Observability: trace viewer, token cost, errors
  • Knowledge store (docs, embeddings, queries)
  • Secure rate limiting + metering
  • Gateway support for multiple AI models and OSS

Long-Term

  • Multi-agent orchestration (optional)
  • Private model hosting gateway
  • Org/team usage controls + billing