Skip to main content

key/value store

Project description

A key/value store implementation in Python, supporting multiple backends, data redundancy and distribution.

Keys

A key (str) can look like:

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

  • Any other pure ASCII string without “/” or “..” or “ “.

Namespaces

To keep stuff apart, keys should get prefixed with a namespace, like:

  • 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 could work without a namespace (namespace “”), but then you can’t add another namespace later, because then you would have created nested namespaces.

Values

Values can be any arbitrary binary data (bytes).

Store Operations

The high-level Store API implementation transparently deals with nesting and soft deletion, so the caller doesn’t have to care much for 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, with or without soft deleted items.

  • store: write a new item into the store (giving its key/value pair)

  • load: read a value from the store (giving its key), partial loads giving offset and/or size are supported.

  • info: get information about an item via its key (exists? size? …)

  • delete: immediately remove an item from the store (giving its key)

  • move: implements rename, soft delete / undelete, move to current nesting level

  • stats: api call counters, time spent in api methods, data volume/throughput

  • latency/bandwidth emulator: can emulate higher latency (via BORGSTORE_LATENCY [us]) and lower bandwidth (via BORGSTORE_BANDWIDTH [bit/s]) than what is actually provided by the backend.

Automatic Nesting

For the Store user, items have names like e.g.:

namespace/0123456789abcdef… namespace/abcdef0123456789…

If there are very many items in the namespace, this could lead to scalability issues in the backend, thus the Store implementation offers transparent nesting, so that internally the Backend API will be called with names like e.g.:

namespace/01/23/56/0123456789abcdef… 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.

Soft deletion

To soft delete an item (so its value could be still read or it could 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 have a boolean flag “deleted” to choose whether they shall consider soft deleted items.

Backends

The backend API is rather simple, one only needs to provide some very basic operations.

Currently, these storage backends are implemented:

  • POSIX filesystems (namespaces: directories, values: in key-named files)

  • SFTP (access a server via sftp, namespaces: directories, values: in key-named files)

  • (more might come in future)

MStore

API of MStore is very similar to Store, but instead of directly using one backend only (like Store does), it uses multiple Stores internally to implement:

  • redundancy (keep same data at multiple places)

  • distribution (keep different data at multiple places)

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 (like: more than backend limitations). Usually this is not a problem though.

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

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

Want a demo?

Run this to get instructions how to run the demo:

python3 -m borgstore

State of this project

API is still unstable and expected to change as development goes on.

There will be no data migration tools involving development/testing releases, like e.g. upgrading a store from alpha1 to alpha2 or beta13 to release.

There are tests and they succeed for the basic functionality, so some of the stuff is already working well.

There might be missing features or optimization potential, feedback welcome!

There are a lot of possible, but still missing backends (like e.g. for cloud storage). If you want to create and support one: pull requests are welcome.

Borg?

Please note that this code is currently not used by the stable release of BorgBackup (aka “borg”), but only by borg2 beta 10+ and master branch.

License

BSD license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

borgstore-0.0.3.tar.gz (20.2 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page