# Store

## Overview

The high-level Store API implementation transparently deals with nesting and soft deletion, so the caller doesn’t need to care much about that, and the backend API can be much simpler:

- create/destroy: initialize or remove the whole store.

- list: flat list of the items in the given namespace (by default, only non-deleted items; optionally, only soft-deleted items).

- store: write a new item into the store (providing its key/value pair).

- load: read a value from the store (given its key); partial loads specifying an offset and/or size are supported.

- info: get information about an item via its key (exists, size, …).

- hash: computes the hexdigest for the content of an item (given its key).

- delete: immediately remove an item from the store (given its key).

- move: implements renaming, soft delete/undelete, and moving to the current nesting level.

- defrag: general purpose defragmentation helper (copies blocks to new items)

- quota: return quota limit and usage (-1 if quotas not enabled or not supported)

- stats: API call counters, time spent in API methods, data volume/throughput.

- latency/bandwidth emulator: see Latency and bandwidth emulator.

Store operations (and per-op timing and volume) are logged at DEBUG log level.

See also Store caching for optional Store-level caching with a secondary backend.

## Latency and bandwidth emulator

The Store can emulate slower backend behavior using environment variables:

- `BORGSTORE_LATENCY`: per-primary-call latency in microseconds (`[us]`).

- `BORGSTORE_BANDWIDTH`: primary-call bandwidth limit in bits per second (`[bit/s]`).

Current behavior with Store caching enabled:

- Emulation applies to primary backend operations.

- Emulation does not apply to cache backend operations.

This means:

- On cache miss paths (for example writethrough/mirror reads that load from the primary backend), emulation affects the primary backend calls.

- On cache hit paths, cached reads avoid primary backend load operations and therefore do not incur emulated bandwidth delay for the cache backend read.

- Name resolution for Store operations still uses primary backend lookups, therefore configured latency can still be visible even when data comes from cache.

## Keys

A key (str) can look like:

- 0123456789abcdef… (usually a long, hex-encoded hash value)

- Any other pure ASCII string without ‘/’, ‘..’, or spaces.

## Namespaces

To keep things separate, keys should be prefixed with a namespace, such as:

- config/settings

- meta/0123456789abcdef…

- data/0123456789abcdef…

Please note:

1. You should always use namespaces.

2. Nested namespaces like namespace1/namespace2/key are not supported.

3. The code can work without a namespace (empty namespace “”), but then you can’t add another namespace later, because that would create nested namespaces.

## Values

Values can be any arbitrary binary data (bytes).

## Automatic Nesting

For the Store user, items have names such as:

- namespace/0123456789abcdef…

- namespace/abcdef0123456789…

If there are very many items in the namespace, this could lead to scalability issues in the backend. The Store implementation therefore offers transparent nesting, so that internally the backend API is called with names such as:

- namespace/01/23/45/0123456789abcdef…

- namespace/ab/cd/ef/abcdef0123456789…

The nesting depth can be configured from 0 (= no nesting) to N levels and there can be different nesting configurations depending on the namespace.

The Store supports operating at different nesting levels in the same namespace at the same time.

When using nesting depth > 0, the backends assume that keys are hashes (contain hex digits) because some backends pre-create the nesting directories at initialization time to optimize backend performance.

## Soft deletion

To soft-delete an item (so its value can still be read or it can be undeleted), the store just renames the item, appending “.del” to its name.

Undelete reverses this by removing the “.del” suffix from the name.

Some store operations provide a boolean flag “deleted” to control whether they consider soft-deleted items.

## Scalability

- Count of key/value pairs stored in a namespace: automatic nesting is provided for keys to address common scalability issues.

- Key size: there are no special provisions for extremely long keys (e.g., exceeding backend limitations). Usually this is not a problem, though.

- Value size: there are no special provisions for dealing with large value sizes (e.g., more than available memory, more than backend storage limitations, etc.). If one deals with very large values, one usually cuts them into chunks before storing them in the store.

- Partial loads improve performance by avoiding a full load if only part of the value is needed (e.g., a header with metadata).