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), and use the same on-disk layout (memory's "disk" is a JS Map).

Quick start

import { Brainy } from '@soulcraft/brainy'

// Filesystem (recommended for any persistent workload):
const brain = new Brainy({
  storage: { type: 'filesystem', rootDirectory: './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

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):

# 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.

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

// BrainyConfig['storage'] — either a config object or a pre-constructed adapter:
storage?:
  | {
      // The adapter type. Defaults to 'auto'
      // (filesystem on Node-like runtimes, memory otherwise).
      type: 'auto' | 'memory' | 'filesystem'

      // Root directory for filesystem storage. Passed through to storage
      // factories, including plugin-provided ones.
      rootDirectory?: string

      // Adapter-specific options.
      options?: any
    }
  | StorageAdapter   // e.g. storage: new MemoryStorage()

Direct construction

If you want to skip the factory:

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', rootDirectory: '/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.