dWeb University

dAppDB Guide

DappDB Architecture

DappDB is a scalable peer-to-peer key-value database for the distributed web protocol (dweb://) and other distributed web protocols.

Filesystem metaphor

DappDB is structured to be used much like a traditional hierarchical
filesystem. A value can be written and read at locations like /foo/bar/baz,
and the API supports querying or tracking values at subpaths, like how watching
for changes on /foo/bar will report both changes to /foo/bar/baz and also

Set of append-only logs (feeds)

A DappDB is fundamentally a set of
@ddatabase/cores. A @ddatabase/core is a secure
append-only log that is identified by a public key, and can only be written to
by the holder of the corresponding private key. Because it is append-only, old
values cannot be deleted nor modified. Because it is secure, a feed can be
downloaded from even untrustworthy peers and verified to be accurate. Any
modifications (malicious or otherwise) to the original feed data by someone
other than the author can be readily detected.

Each entry in a @ddatabase/core has a sequence number, that increments by 1 with
each write, starting at 0 (seq=0).

DappDB builds its hierarchical key-value store on top of these @ddatabase/core feeds,
and also provides facilities for authorization, and replication of those member

Directed acyclic graph

The combination of all operations performed on a DappDB by all of its members
forms a DAG (directed acyclic graph). Each write to the database (setting a
key to a value) includes information to point backward at all of the known
"heads" in the graph.

To illustrate what this means, let's say Alice starts a new DappDB and writes 2
values to it:

// Feed

0 (/foo/bar = 'baz')
1 (/foo/2   = '{ "some": "json" }')

// Graph

Alice:  0  <---  1

Where sequence number 1 (the second entry) refers to sequence number 0 on the
same feed (Alice's).

Now Alice authorizes Bob to write to the DappDB. Internally, this means Alice
writes a special message to her feed saying that Bob's feed (identified by his
public key) should be read and replicated in by other participants. Her feed

// Feed

0 (/foo/bar = 'baz')
1 (/foo/2   = '{ "some": "json" }')
2 (''       = '')

// Graph

Alice: 0  <---  1  <---  2

Authorization is formatted internally in a special way so that it isn't
interpreted as a key/value pair.

Now Bob writes a value to his feed, and then Alice and Bob sync. The result is:

// Feed

//// Alice
0 (/foo/bar = 'baz')
1 (/foo/2   = '{ "some": "json" }')
2 (''       = '')

//// Bob
0 (/a/b     = '12')

// Graph

Alice: 0  <---  1  <---  2
Bob  : 0

Notice that none of Alice's entries refer to Bob's, and vice versa. This is
because neither has written any entries to their feeds since the two became
aware of each other (authorized & replicated each other's feeds).

Right now there are two "heads" of the graph: Alice's feed at seq 2, and Bob's
feed at seq 0.

Next, Alice writes a new value, and her latest entry will refer to Bob's:

// Feed

//// Alice
0 (/foo/bar = 'baz')
1 (/foo/2   = '{ "some": "json" }')
2 (''       = '')
3 (/foo/hup = 'beep')

//// Bob
0 (/a/b     = '12')

// Graph

Alice: 0  <---  1  <---  2  <--/  3
Bob  : 0  <-------------------/

Because Alice's latest feed entry refers to Bob's latest feed entry, there is
now only one "head" in the database. That means there is enough information in
Alice's seq=3 entry to find any other key in the database. In the last example,
there were two heads (Alice's seq=2 and Bob's seq=0); both of which would need
to be read internally in order to locate any key in the database.

Now there is only one "head": Alice's feed at seq 3.


The set of @ddatabase/cores are authorized in that the original author of the first
@ddatabase/core in a hyperdb must explicitly denote in their append-only log that the
public key of a new @ddatabase/core is permitted to edit the database. Any authorized
member may authorize more members. There is no revocation or other author
management elements currently.

Incremental index

DappDB builds an incremental index with every new key/value pairs ("nodes")
written. This means a separate data structure doesn't need to be maintained
elsewhere for fast writes and lookups: each node written has enough information
to look up any other key quickly and otherwise navigate the database.

Each node stores the following basic information:

  • key: the key that is being created or modified. e.g. /home/sww/dev.md
  • value: the value stored at that key.
  • seq: the sequence number of this entry in the owner's @ddatabase/core. 0 is the
    first, 1 the second, and so forth.
  • feed: the ID of the @ddatabase/core writer that wrote this
  • path: a 2-bit hash sequence of the key's components
  • trie: a navigation structure used with path to find a desired key
  • clock: vector clock to determine node insertion causality
  • feeds: an array of { feedKey, seq } for decoding a clock

Vector clock

Each node stores a vector clock of
the last known sequence number from each feed it knows about. This is what forms
the DAG structure.

A vector clock on a node of, say, [0, 2, 5] means:

  • when this node was written, the largest seq # in my local fed is 0
  • when this node was written, the largest seq # in the second feed I have is 2
  • when this node was written, the largest seq # in the third feed I have is 5

For example, Bob's vector clock for Alice's seq=3 entry above would be [0, 3]
since he knows of her latest entry (seq=3) and his own (seq=0).

The vector clock is used for correctly traversing history. This is necessary for
the db#heads API as well as db#createHistoryStream.

Prefix trie

Given a DappDB with hundreds of entries, how can a key like /a/b/c be looked
up quickly?

Each node stores a prefix trie that
assists with finding the shortest path to the desired key.

When a node is written, its prefix hash is computed. This done by first
splitting the key into its components (a, b, and c for /a/b/c), and then
hashing each component into a 32-character hash, where one character is a 2-bit
value (0, 1, 2, or 3). The prefix hash for /a/b/c is

node.path = [
1, 2, 0, 1, 2, 0, 2, 2, 3, 0, 1, 2, 1, 3, 0, 3, 0, 0, 2, 1, 0, 2, 0, 0, 2, 0, 0, 3, 2, 1, 1, 2,
0, 1, 2, 3, 2, 2, 2, 0, 3, 1, 1, 3, 0, 3, 1, 3, 0, 1, 0, 1, 3, 2, 0, 2, 2, 3, 2, 2, 3, 3, 2, 3,
0, 1, 1, 0, 1, 2, 3, 2, 2, 2, 0, 0, 3, 1, 2, 1, 3, 3, 3, 3, 3, 3, 0, 3, 3, 2, 3, 2, 3, 0, 1, 0,
4 ]

Each component is divided by a newline. 4 is a special value indicating the
end of the prefix.


Consider a fresh DappDB. We write /a/b = 24 and get back this node:

{ key: '/a/b',
  value: '24',
  clock: [ 0 ],
  trie: [],
  feeds: [ [Object] ],
  feedSeq: 0,
  feed: 0,
  seq: 0,
   [ 1, 2, 0, 1, 2, 0, 2, 2, 3, 0, 1, 2, 1, 3, 0, 3, 0, 0, 2, 1, 0, 2, 0, 0, 2, 0, 0, 3, 2, 1, 1, 2,
     0, 1, 2, 3, 2, 2, 2, 0, 3, 1, 1, 3, 0, 3, 1, 3, 0, 1, 0, 1, 3, 2, 0, 2, 2, 3, 2, 2, 3, 3, 2, 3,
     4 ] }

If you compare this path to the one for /a/b/c above, you'll see that the
first 64 2-bit characters match. This is because /a/b is a prefix of /a/b/c.

Since this is the first entry, seq is 0. Since this is the only known feed,
feed is also 0. feeds is an array of entries of the form { key: Buffer, seq: Number } that let you map the numeric value feed to a @ddatabase/core key and
its sequence number head. feeds isn't always set: it only gets included when
it changes compared to node.seq - 1, in the interest of storing less data per

Now we write /a/c = hello and get this node:

{ key: '/a/c',
  value: 'hello',
  clock: [ 0 ],
  trie: [ , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , [ , , [ { feed: 0, seq: 0 } ] ] ],
  feeds: [],
  feedSeq: 0,
  feed: 0,
  seq: 1,
   [ 1, 2, 0, 1, 2, 0, 2, 2, 3, 0, 1, 2, 1, 3, 0, 3, 0, 0, 2, 1, 0, 2, 0, 0, 2, 0, 0, 3, 2, 1, 1, 2,
     0, 1, 1, 0, 1, 2, 3, 2, 2, 2, 0, 0, 3, 1, 2, 1, 3, 3, 3, 3, 3, 3, 0, 3, 3, 2, 3, 2, 3, 0, 1, 0,
     4 ] }

As expected, this node has the same feed value as before (since we're only
writing to one feed). Its seq is 1, since the last was 0. Notice that feeds
isn't included, because the mapping of the numeric feed value to a key hasn't

Also, this and the previous node have the first 32 characters of their path in
common (the prefix /a).

Notice though that trie is set. It's a long but sparse array. It has 35
entries, with the last one referencing the first node inserted (a/b/). Why?

(If it wasn't stored as a sparse array, you'd actually see 64 entries (the
length of the path). But since the other 29 entries are also empty, hyperdb
doesn't bother allocating them.)

If you visually compare this node's path with the previous node's path, how
many entries do they have in common? At which entry do the 2-bit numbers

At the 35th entry.

What this is saying is "if the hash of the key you're looking for differs from
mine on the 35th entry, you want to travel to { feed: 0, seq: 0 } to find the
node you're looking for.

This is how finding a node works, starting at any other node:

  1. Compute the 2-bit hash sequence of the key you're after (e.g. a/b)
  2. Lookup the newest entry in the feed.
  3. Compare its path against the hash you just computed.
  4. If you discover that the path and your hash match, then this is the node
    you're looking for!
  5. Otherwise, once a 2-bit character from path and your hash disagree, note
    the index # where they differ and look up that value in the node's trie.
    Fetch that node at the given feed and sequence number, and go back to step 3.
    Repeat until you reach step 4 (match) or there is no entry in the node's trie
    for the key you're after (no match).

What if there are multiple feeds in the DappDB? The lookup algorithm changes
slightly. Replace the above step 2 for:

  1. Fetch the latest entry from every feed. For each head node, proceed to
    the next step.

The other steps are the same as before.

dAppDB Implementation

Distributed scalable database for the distributed web protocol (dweb://).

npm config set @dappdb:registry http://npm.dwebs.io
npm install @dappdb/core

Read ARCHITECTURE.md for details on how dAppDB works.


var dappdb = require('@dappdb/core')

var db = dappdb('./my.db', {valueEncoding: 'utf-8'})

db.put('/hello', 'world', function (err) {
  if (err) throw err
  db.get('/hello', function (err, nodes) {
    if (err) throw err
    console.log('/hello --> ' + nodes[0].value)


var db = dappdb(storage, [key], [options])

Create a new dAppDB.

storage can be a string or a function. If a string like the above example, the
random-access-file storage
module is used; the resulting folder with the data will be whatever storage is
set to.

If storage is a function, it will be called with every filename dAppDB needs
to operate on. There are many providers for the
interface. e.g.

var ram = require('random-access-memory')
var feed = dappdb(function (filename) {
  // filename will be one of: data, bitfield, tree, signatures, key, secret_key
  // the data file will contain all your data concattenated.

  // just store all files in ram by returning a random-access-memory instance
  return ram()

key is a Buffer containing the local feed's public key. If you do not set
this the public key will be loaded from storage. If no key exists a new key pair
will be generated.

Options include:

  map: node => mappedNode, // map nodes before returning them
  reduce: (a, b) => someNode, // reduce the nodes array before returning it
  firstNode: false, // set to true to reduce the nodes array to the first node in it
  valueEncoding: 'binary' // set the value encoding of the db


Buffer containing the public key identifying this dAppDB.

Populated after ready has been emitted. May be null before the event.


Buffer containing a key derived from the db.key.
In contrast to db.key this key does not allow you to verify the data but can be used to announce or look for peers that are sharing the same dAppDB, without leaking the dAppDB key.

Populated after ready has been emitted. May be null before the event.


Emitted exactly once: when the db is fully ready and all static properties have
been set. You do not need to wait for this when calling any async functions.


Get the current version identifier as a buffer for the db.

var checkout = db.checkout(version)

Checkout the db at an older version. The checkout is a DB instance as well.
Version should be a version identifier returned by the db.version api or an
array of nodes returned from db.heads.

db.put(key, value, [callback])

Insert a new value. Will merge any previous values seen for this key.

db.get(key, callback)

Lookup a string key. Returns a nodes array with the current values for this key.
If there is no current conflicts for this key the array will only contain a single node.

db.del(key, callback)

Delete a string key.

db.batch(batch, [callback])

Insert a batch of values efficiently, in a single atomic transaction. A batch should be an array of objects that look like this:

  type: 'put',
  key: someKey,
  value: someValue

callback's parameters are err, nodes, where nodes is an array of the batched nodes.


Your local writable feed. You have to get an owner of the dAppDB to authorize you to have your
writes replicate. The first person to create the dAppDB is the first owner.

db.authorize(key, [callback])

Authorize another peer to write to the dAppDB.

To get another peer to authorize you you'd usually do something like

myDb.on('ready', function () {
  console.log('You local key is ' + myDb.local.key.toString('hex'))
  console.log('Tell an owner to authorize it')

db.authorized(key, [callback])

Check whether a key is authorized to write to the database.

myDb.authorized(otherDb.local.key, function (err, auth) {
  if (err) console.log('err', err)
  else if (auth === true) console.log('authorized')
  else console.log('not authorized')

watcher = db.watch(folderOrKey, onchange)

Watch a folder and get notified anytime a key inside this folder
has changed.

db.watch('foo/bar', function () {
  console.log('folder has changed')


db.put('foo/bar/baz', 'hi') // triggers the above

You can destroy the watcher by calling watcher.destroy().

The watcher will emit watching when it starts watching and change
when a change has been detected.

If a critical error occurs an error will be emitted on the watcher.

var stream = db.createReadStream(prefix[, options])

Create a readable stream of nodes stored in the database.
Set prefix to only iterate nodes prefixed with that folder.

Options include:

  recursive: true // visit all subfolders.
                  // set to false to only visit the first node in each folder
  reverse: true   // read the records in reverse order.
  gt: false       // visit only strictly nodes that are > than the prefix

var stream = db.createWriteStream()

Create a writable stream.

Where stream.write(data) accepts data as an object or an array of objects with the same form as db.batch().

db.list(prefix[, options], callback)

Same as createReadStream but buffers the result to a list that is passed to the

var stream = db.createDiffStream(prefix[, checkout)

Find out about changes in key/value pairs between the version checkout and
current version prefixed by prefix.

stream is a readable object stream that outputs modifications like

{ left: nodes, right: nodes }

left are the nodes for a key found in the db and right are the nodes found in the checkout.
If no nodes exist in the db for the key left will be null and vice versa.

var stream = db.createHistoryStream([options])

Returns a readable stream of node objects covering all historic values since the beginning of time.

Nodes are emitted in topographic order, meaning if value v2 was aware of value
v1 at its insertion time, v1 must be emitted before v2.

To emit the nodes in reverse order pass {reverse: true} as an option.

var stream = db.createKeyHistoryStream(key)

Returns a readable stream of node objects covering all historic values for a specific key.

Results are returned with the latest value first.

var stream = db.replicate([options])

Create a replication stream. Options include:

  live: false // set to true to keep replicating



Updated about a year ago

dAppDB Guide

Suggested Edits are limited on API Reference Pages

You can only suggest edits to Markdown body content, but not to the API spec.