open-brainy/docs/guides/storage-adapters.md

---
title: Storage Adapters
slug: guides/storage-adapters
public: true
category: guides
template: guide
order: 2
description: "Two adapters cover every deployment: in-memory for tests + ephemeral workloads, filesystem for everything that needs to persist. Both share one on-disk contract, including generational history and snapshots. Cloud backup is operator tooling, not a built-in adapter."
next:
  - guides/plugins
  - concepts/consistency-model
---

# Storage Adapters

Brainy 8.0 ships **two storage adapters**:

- **`FileSystemStorage`** — persistent on-disk storage. The default for any
  deployment that needs to survive a restart. Runs on Node.js, Bun, and Deno.
- **`MemoryStorage`** — in-memory only. The right choice for tests, ephemeral
  workloads, and short-lived demos.

Both implement the same `StorageAdapter` interface, support the full Db API
(generational history, snapshots, restore — see the
[consistency model](../concepts/consistency-model.md)), and use the same
on-disk layout (memory's "disk" is a JS Map).

## Quick start

```ts
import { Brainy } from '@soulcraft/brainy'

// Filesystem (recommended for any persistent workload):
const brain = new Brainy({
  storage: { type: 'filesystem', path: './brainy-data' }
})

// Memory (tests, ephemeral):
const brainMem = new Brainy({ storage: { type: 'memory' } })

// Auto-detect (filesystem on Node-like runtimes, memory in browsers):
const brainAuto = new Brainy({ storage: { type: 'auto' } })
```

## When to use which

| Use case | Adapter | Why |
|---|---|---|
| Production app | `filesystem` | Durable, snapshot-able, mmap-able |
| Tests, CI | `memory` | No disk teardown; fast |
| Short-lived data pipeline | `memory` | No persistence needed |
| In-browser demo | `memory` | Filesystem unavailable in browsers |
| Cloud deployment | `filesystem` on local disk + operator backup | See "Cloud backup" below |

## Cloud backup — operator tooling, not a built-in

Brainy 8.0 deliberately ships **no cloud storage adapters**. Cloud backup is
handled at the operator layer with standard tooling, the same pattern every
production database uses (Postgres, SQLite, Redis):

```bash
# After a brainy flush, sync the on-disk artefact to your cloud of choice.
gsutil rsync -r /var/lib/brainy gs://my-backup-bucket/brainy/
# or:
aws s3 sync /var/lib/brainy s3://my-backup-bucket/brainy/
# or:
rclone sync /var/lib/brainy remote:brainy-backups/
# or:
azcopy sync /var/lib/brainy "https://account.blob.core.windows.net/brainy?sv=..."
```

Brainy's filesystem layout is sync-friendly:
- Atomic writes (temp + rename) — readers never see torn files
- Per-shard files — `rsync`-style incremental sync works well
- Immutable generation records (`_generations/`) — append-only, cache-friendly

For point-in-time backups, take a filesystem snapshot (ZFS, btrfs, LVM, EBS,
etc.) or use `brain.now().persist(path)` to write a self-contained snapshot
you can sync independently of the live brain — see
[Snapshots & Time Travel](./snapshots-and-time-travel.md).

## Why no cloud adapters in 8.0?

Cloud storage adapters lived in Brainy 4.x-7.x. They were dropped in 8.0
because:

- Zero production consumers used them at scale — every known production
  deployment ran on local filesystem.
- Cloud-storage HNSW / DiskANN doesn't perform — vector indexes need
  low-latency random reads that S3 / GCS / R2 / Azure can't provide
  consistently.
- Bundling cloud SDKs into the library cost ~3000-5000 LOC + 4-7 transitive
  dependencies for a feature nobody used.
- Cloud backup via operator tooling is strictly more reliable than in-app
  upload (better retry semantics, better observability, better cost control).

Brainy 8.0 is smaller, faster to install, and clearer about what it does.

## Configuration

```ts
// BrainyConfig['storage'] — either a config object or a pre-constructed adapter:
storage?:
  | {
      // The adapter type. Optional — a top-level `path` implies 'filesystem',
      // so { path: '/data' } works without it. Defaults to 'auto'
      // (filesystem on Node-like runtimes, memory otherwise).
      type?: 'auto' | 'memory' | 'filesystem'

      // CANONICAL directory for filesystem storage. The rest of the API already
      // speaks `path` (persist(path), Brainy.load(path), asOf(path),
      // restore(path)). Specifying it implies type: 'filesystem'. Passed through
      // to storage factories, including plugin-provided ones.
      path?: string

      // REMOVED in 8.0 — passing `rootDirectory` THROWS. Use `path`.
      rootDirectory?: string

      // REMOVED in 8.0 — a nested `options.{path,rootDirectory}` THROWS. Use `path`.
      options?: any
    }
  | StorageAdapter   // e.g. storage: new MemoryStorage()
```

The canonical — and only — key is the top-level **`path`**. The pre-8.0 aliases
`rootDirectory`, `options.{path,rootDirectory}`, and
`fileSystemStorage.{path,rootDirectory}` were **removed in 8.0**: passing one now
throws with the exact rename (never a silent default that would misplace data on
upgrade). Because `path` implies filesystem, `{ path: '/data' }` is a complete
config; the `type` is optional.

## Direct construction

If you want to skip the factory:

```ts
import { FileSystemStorage, MemoryStorage } from '@soulcraft/brainy'

const fsStorage = new FileSystemStorage('./brainy-data')
const memStorage = new MemoryStorage()

const brain = new Brainy({ storage: fsStorage })
```

## Migration from 7.x cloud adapters

7.x consumers of `OPFSStorage`, `GcsStorage`, `R2Storage`, `S3CompatibleStorage`,
or `AzureBlobStorage` need to migrate to `FileSystemStorage` plus operator
backup tooling. The recipe:

1. On the host running Brainy, mount a local disk (NVMe recommended). Cloud
   providers all expose persistent local disks: GCP Persistent Disk, AWS EBS,
   Azure Managed Disks.
2. Set `storage: { type: 'filesystem', path: '/mnt/brainy-data' }`.
3. Run your existing data import once into the new local store.
4. Set up an operator backup job using `gsutil` / `aws s3` / `rclone` /
   `azcopy` on a cron — hourly or whatever your RPO requires. Point it at
   the brainy data dir.
5. For point-in-time backups, use filesystem snapshots or
   `brain.now().persist(path)`.

Same data, same APIs, no library-side cloud code.