quadstore
v13.2.4
Published
Quadstore is a LevelDB-backed RDF graph database / triplestore for JavaScript runtimes (browsers, Node.js, Deno, Bun, ...) that implements the RDF/JS interfaces and supports SPARQL queries and querying across named graphs.
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QUADSTORE
Quadstore is a LevelDB-backed RDF graph database / triplestore for JavaScript runtimes (browsers, Node.js, Deno, Bun, ...) written in TypeScript.
- Implements the
Sink
,Source
andStore
RDF/JS interfaces for maximum interoperability with other RDF libraries - Supports SPARQL queries via quadstore-comunica, a tailored configuration and distribution of the Comunica querying framework
- Natively capable of querying across named graphs
Table of contents
- QUADSTORE
- Table of contents
- Example of basic usage
- Status
- Usage
- Parsing and serializing RDF
- Storage backends
- Data model and return values
- Quadstore class
- Access to the backend
- Quadstore.prototype.open()
- Quadstore.prototype.close()
- Quadstore.prototype.get()
- Range matching
- Quadstore.prototype.put()
- Quadstore.prototype.multiPut()
- Quadstore.prototype.del()
- Quadstore.prototype.multiDel()
- Quadstore.prototype.patch()
- Quadstore.prototype.multiPatch()
- Quadstore.prototype.getStream()
- Quadstore.prototype.putStream()
- Quadstore.prototype.delStream()
- Quadstore.prototype.match()
- Quadstore.prototype.import()
- Quadstore.prototype.remove()
- Quadstore.prototype.removeMatches()
- Blank nodes and quad scoping
- SPARQL
- Browser usage
- Deno usage
- Performance
- LICENSE
Example of basic usage
import { MemoryLevel } from 'memory-level';
import { DataFactory } from 'rdf-data-factory';
import { Quadstore } from 'quadstore';
import { Engine } from 'quadstore-comunica';
// Any implementation of AbstractLevel can be used.
const backend = new MemoryLevel();
// Implementation of the RDF/JS DataFactory interface
const df = new DataFactory();
// Store and query engine are separate modules
const store = new Quadstore({backend, dataFactory: df});
const engine = new Engine(store);
// Open the store
await store.open();
// Put a single quad into the store using Quadstore's API
await store.put(df.quad(
df.namedNode('http://example.com/subject'),
df.namedNode('http://example.com/predicate'),
df.namedNode('http://example.com/object'),
df.defaultGraph(),
));
// Retrieves all quads using Quadstore's API
const { items } = await store.get({});
// Retrieves all quads using RDF/JS Stream interfaces
const quadsStream = store.match(undefined, undefined, undefined, undefined);
quadsStream.on('data', quad => console.log(quad));
// Queries the store via RDF/JS Query interfaces
const bindingsStream = await engine.queryBindings('SELECT * {?s ?p ?o}');
bindingsStream.on('data', binding => console.log(binding));
Status
Active, under development.
Changelog
See CHANGELOG.md.
Roadmap
We're currently working on the following features:
- optimizing SPARQL performance by pushing filters down from the engine to the persistence layer
We're also evaluating the following features for future developments:
- RDF* (see also these slides)
Notes
- uses Semantic Versioning, pre-releases are tagged accordingly;
- requires Node.js >= 16.0.0.
Usage
Parsing and serializing RDF
quadstore
is compatible with all parsers and serializers implementing the
relevant RDF/JS interfaces, such as n3 and @rdfjs/formats.
See https://rdf.js.org for an open list of such libraries.
For example, here is how to use n3 in order to parse a Turtle file
into an instance of Quadstore
in a streaming fashion, with full backpressure
handling, using classic-level
as the backend:
import { Quadstore } from 'quadstore';
import { ClassicLevel } from 'classic-level';
import { DataFactory, StreamParser } from 'n3';
const store = new Quadstore({
backend: new ClassicLevel('/path/to/db'),
dataFactory: DataFactory,
});
await store.open();
const reader = fs.createReadStream('/path/to/file.ttl');
const parser = new StreamParser({ format: 'text/turtle' });
await store.putStream(reader.pipe(parser), { batchSize: 100 });
await store.close();
quadstore
does not include any RDF parsing and/or serialization capability
by choice as no subset of formats would meet the requirements of every use
case and shipping support for all mainstream RDF formats would result in
exceedingly high bundle sizes.
Storage backends
quadstore
can work with any storage backend that implements the
AbstractLevel interface. An incomplete list of available backends
is available at level/awesome#stores.
Note that quadstore is only compatible with abstract-level
's API as of
its 1.x
versions. Packages whose semver major version number tracks that
of abstract-level
, such as classic-level
and memory-level
, must be
used up to their most recent 1.x
version. The switch to abstract-level
version 2.x
is tracked in #168.
Our test suite focuses on the following backends:
classic-level
for persistent, on-disk storage using LevelDBmemory-level
for volatile in-memory storage using red-black trees- ~~
rocksdb
for persistent storage using RocksDB~~- waiting for the
rocks-level
package to be published
- waiting for the
@nxtedition/rocks-level
for persistent, on-disk storage using RocksDB- this is an alternative backend for RocksDB that tends to be 5% - 15%
faster then
classic-level
but is maintained outside of the Level community and set of official packages
- this is an alternative backend for RocksDB that tends to be 5% - 15%
faster then
browser-level
for browser-side persistent storage using IndexedDB. For more information about browser-side usage, see the Browser usage section
Data model and return values
Except for those related to the RDF/JS stream interfaces, quadstore
's
API is promise-based and all methods return objects that include both the actual
query results and the relevant metadata.
Objects returned by quadstore
's APIs have the type
property set to one of
the following values:
"VOID"
- when there's no data returned by the database, such as with theput
method;"QUADS"
- when a query returns a collection of quads;"APPROXIMATE_SIZE"
- when a query returns an approximate count of how many matching items are present.
For those methods that return objects with the type
property set to
"QUADS"
, quadstore
provides query results either in streaming mode or in
non-streaming mode.
Streaming methods such as getStream
return objects with the iterator
property set to an instance of AsyncIterator
, an implementation of a
subset of the stream.Readable
interface.
Non-streaming methods such as get
return objects with the items
property
set to an array of quads.
Quads are returned as and expected to be instances of the
RDF/JS Quad
interface as produced by the implementation of the
RDF/JS DataFactory
interface passed to the Quadstore
constructor.
Matching patterns, such as those used in the get
and getStream
methods,
are expected to be maps of term names to instances of the
RDF/JS Term interface.
Quadstore class
const Quadstore = require('quadstore').Quadstore;
const store = new Quadstore(opts);
Instantiates a new store. Supported properties for the opts
argument
are:
opts.backend
The opts.backend
option must be an instance of a leveldb backend.
See storage backends.
opts.dataFactory
The dataFactory
option must be an implementation of the
RDF/JS DataFactory interface. Some of the available
implementations:
opts.indexes
The opts.indexes
option allows users to configure which indexes will be used
by the store. If not set, the store will default to the following indexes:
[
['subject', 'predicate', 'object', 'graph'],
['object', 'graph', 'subject', 'predicate'],
['graph', 'subject', 'predicate', 'object'],
['object', 'subject', 'predicate', 'graph'],
['predicate', 'object', 'graph', 'subject'],
['graph', 'predicate', 'object', 'subject'],
];
This option, if present, must be set to an array of term arrays, each of
which must represent one of the 24 possible permutations of the four terms
subject
, predicate
, object
and graph
. Partial indexes are not
supported.
The store will automatically select which index(es) to use for a given query based on the available indexes and the query itself. If no suitable index is found for a given query, the store will throw an error.
opts.prefixes
Also, Quadstore
can be configured with a prefixes
object that defines a
reversible mapping of IRIs to abbreviated forms, with the intention of reducing
the storage cost where common HTTP prefixes are known in advance.
The prefixes
object defines a bijection using two functions expandTerm
and
compactIri
, both of which take a string parameter and return a string, as in
the following example:
opts.prefixes = {
expandTerm: term => term.replace(/^ex:/, 'http://example.com/'),
compactIri: iri => iri.replace(/^http:\/\/example\.com\//, 'ex:'),
}
This will replace the IRI http://example.com/a
with ex:a
in storage.
Access to the backend
The backend of a quadstore
can be accessed with the db
property, to perform
additional storage operations independently of quads.
In order to perform write operations atomically with quad storage, the put
,
multiPut
, del
, multiDel
, patch
and multiPatch
methods accept a
preWrite
option which defines a procedure to augment the batch, as in the
following example:
await store.put(dataFactory.quad(/* ... */), {
preWrite: batch => batch.put('my.key', Buffer.from('my.value'))
});
Quadstore.prototype.open()
This method opens the store and throws if the open operation fails for any reason.
Quadstore.prototype.close()
This method closes the store and throws if the open operation fails for any reason.
Quadstore.prototype.get()
const pattern = {graph: dataFactory.namedNode('ex://g')};
const { items } = await store.get(pattern);
Returns an array of all quads within the store matching the specified terms.
This method also accepts an optional opts
parameter with the following
optional properties:
opts.order
: array of term names (e.g.['object']
) that represents the desired ordering criteria of returned quads. Equivalent to theORDER BY
clause inSQL
.opts.reverse
: boolean value that indicates whether to return quads in ascending or descending order. Equivalent toASC
/DESC
modifiers inSQL
.opts.limit
: limit the number of returned quads to the specified value. Equivalent toLIMIT
clause inSQL
.
Range matching
quadstore
supports range-based matching in addition to value-based matching.
Ranges can be defined using the gt
, gte
, lt
, lte
properties:
const pattern = {
object: {
termType: 'Range',
gt: dataFactory.literal('7', 'http://www.w3.org/2001/XMLSchema#integer')
}
};
const { items } = await store.get(matchTerms);
Values for literal terms with the following numeric datatypes are matched against their numerical values rather than their literal representations:
http://www.w3.org/2001/XMLSchema#integer
http://www.w3.org/2001/XMLSchema#decimal
http://www.w3.org/2001/XMLSchema#double
http://www.w3.org/2001/XMLSchema#nonPositiveInteger
http://www.w3.org/2001/XMLSchema#negativeInteger
http://www.w3.org/2001/XMLSchema#long
http://www.w3.org/2001/XMLSchema#int
http://www.w3.org/2001/XMLSchema#short
http://www.w3.org/2001/XMLSchema#byte
http://www.w3.org/2001/XMLSchema#nonNegativeInteger
http://www.w3.org/2001/XMLSchema#unsignedLong
http://www.w3.org/2001/XMLSchema#unsignedInt
http://www.w3.org/2001/XMLSchema#unsignedShort
http://www.w3.org/2001/XMLSchema#unsignedByte
http://www.w3.org/2001/XMLSchema#positiveInteger
This is also the case for terms with the following date/time datatypes:
http://www.w3.org/2001/XMLSchema#dateTime
Quadstore.prototype.put()
await store.put(dataFactory.quad(/* ... */));
Stores a new quad. Does not throw or return an error if the quad already exists.
This method also accepts an optional opts
parameter with the following
properties:
opts.preWrite
: this can be set to a function which accepts a chainedBatch and performs additional backend operations atomically with theput
operation. See Access to the backend for more information.opts.scope
: this can be set to aScope
instance as returned byinitScope()
andloadScope()
. If set, blank node labels will be changed to prevent blank node collisions. See Blank nodes and quad scoping.
Quadstore.prototype.multiPut()
await store.multiPut([
dataFactory.quad(/* ... */),
dataFactory.quad(/* ... */),
]);
Stores new quads. Does not throw or return an error if quads already exists.
This method also accepts an optional opts
parameter with the following
properties:
opts.preWrite
: this can be set to a function which accepts a chainedBatch and performs additional backend operations atomically with theput
operation. See Access to the backend for more information.opts.scope
: this can be set to aScope
instance as returned byinitScope()
andloadScope()
. If set, blank node labels will be changed to prevent blank node collisions. See Blank nodes and quad scoping.
Quadstore.prototype.del()
This method deletes a single quad. It Does not throw or return an error if the specified quad is not present in the store.
await store.del(dataFactory.quad(/* ... */));
This method also accepts an optional opts
parameter with the following
properties:
opts.preWrite
: this can be set to a function which accepts a chainedBatch and performs additional backend operations atomically with theput
operation. See Access to the backend for more information.
Quadstore.prototype.multiDel()
This method deletes multiple quads. It Does not throw or return an error if the specified quads are not present in the store.
await store.multiDel([
dataFactory.quad(/* ... */),
dataFactory.quad(/* ... */),
]);
This method also accepts an optional opts
parameter with the following
properties:
opts.preWrite
: this can be set to a function which accepts a chainedBatch and performs additional backend operations atomically with theput
operation. See Access to the backend for more information.
Quadstore.prototype.patch()
This method deletes one quad and inserts another quad in a single operation. It Does not throw or return an error if the specified quads are not present in the store (delete) or already present in the store (update).
await store.patch(
dataFactory.quad(/* ... */), // will be deleted
dataFactory.quad(/* ... */), // will be inserted
);
This method also accepts an optional opts
parameter with the following
properties:
opts.preWrite
: this can be set to a function which accepts a chainedBatch and performs additional backend operations atomically with theput
operation. See Access to the backend for more information.
Quadstore.prototype.multiPatch()
This method deletes and inserts quads in a single operation. It Does not throw or return an error if the specified quads are not present in the store (delete) or already present in the store (update).
// will be deleted
const oldQuads = [
dataFactory.quad(/* ... */),
dataFactory.quad(/* ... */),
];
// will be inserted
const newQuads = [ // will be inserted
dataFactory.quad(/* ... */),
dataFactory.quad(/* ... */),
dataFactory.quad(/* ... */),
];
await store.multiPatch(oldQuads, newQuads);
This method also accepts an optional opts
parameter with the following
properties:
opts.preWrite
: this can be set to a function which accepts a chainedBatch and performs additional backend operations atomically with theput
operation. See Access to the backend for more information.
Quadstore.prototype.getStream()
const pattern = {graph: dataFactory.namedNode('ex://g')};
const { iterator } = await store.getStream(pattern);
Just as QuadStore.prototype.get(), this method
supports range matching and the order
, reverse
and
limit
options.
Quadstore.prototype.putStream()
await store.putStream(readableStream);
Imports all quads coming through the specified stream.Readable
into the store.
This method also accepts an optional opts
parameter with the following
properties:
opts.scope
: this can be set to aScope
instance as returned byinitScope()
andloadScope()
. If set, blank node labels will be changed to prevent blank node collisions. See Blank nodes and quad scoping.
Quadstore.prototype.delStream()
await store.delStream(readableStream);
Deletes all quads coming through the specified stream.Readable
from the store.
Quadstore.prototype.match()
const subject = dataFactory.namedNode('http://example.com/subject');
const graph = dataFactory.namedNode('http://example.com/graph');
store.match(subject, null, null, graph)
.on('error', (err) => {})
.on('data', (quad) => {
// Quad is produced using dataFactory.quad()
})
.on('end', () => {});
Implementation of the RDF/JS Source#match method. Supports range-based matching.
Quadstore.prototype.import()
const readableStream; // A stream.Readable of Quad() instances
store.import(readableStream)
.on('error', (err) => {})
.on('end', () => {});
Implementation of the RDF/JS Sink#import method.
Quadstore.prototype.remove()
const readableStream; // A stream.Readable of Quad() instances
store.remove(readableStream)
.on('error', (err) => {})
.on('end', () => {});
Implementation of the RDF/JS Store#remove method.
Quadstore.prototype.removeMatches()
const subject = dataFactory.namedNode('http://example.com/subject');
const graph = dataFactory.namedNode('http://example.com/graph');
store.removeMatches(subject, null, null, graph)
.on('error', (err) => {})
.on('end', () => {});
Implementation of the RDF/JS Sink#removeMatches method.
Blank nodes and quad scoping
Blank nodes are defined as existential variables in that they merely indicate the existence of an entity rather than act as references to the entity itself.
While the semantics of blank nodes can be rather confusing, one of the most practical consequences of their definition is that two blank nodes having the same label may not refer to the same entity unless both nodes come from the same logical set of quads.
As an example, here's two JSON-LD documents converted to N-Quads using the
JSON-LD playground:
{
"@id": "http://example.com/bob",
"foaf:knows": {
"foaf:name": "Alice"
}
}
<http://example.com/bob> <foaf:knows> _:b0 .
_:b0 <foaf:name> "Alice" .
{
"@id": "http://example.com/alice",
"foaf:knows": {
"foaf:name": "Bob"
}
}
<http://example.com/alice> <foaf:knows> _:b0 .
_:b0 <foaf:name> "Bob" .
The N-Quads equivalent for both of these documents contains a blank node with
the b0
label. However, although the label is the same, these blank nodes
indicate the existence of two different entities. Intuitively, we can say that
a blank node is scoped to the logical grouping of quads that contains it, be it
a single quad, a document or a stream.
As quadstore treats all write operations as if they were happening within the same scope, importing these two sets of quads would result in a collision of two unrelated blank nodes, leading to a corrupted dataset.
A good way to address these issues is to skolemize skolemize all blank nodes into IRIs / named nodes. However, this is not always possible and / or practical.
The initScope()
method returns a Scope
instance which can be passed to the put
, multiPut
and putStream
methods.
When doing so, quadstore will replace each occurrence of a given blank node
with a different blank node having a randomly-generated label, preventing blank
node collisions.
Each Scope
instance keeps an internal cache of mappings between previously
encountered blank nodes and their replacements, so that it is able to always
return the same replacement blank node for a given label. Each new mapping is
atomically persisted to the store together with its originating quad, leading
each scope to be incrementally persisted to the store consistently with each
successful put
and multiPut
operation. This allows scopes to be re-used
even across process restarts via the
loadScope()
method.
Quadstore.prototype.initScope()
Initializes a new, empty scope.
const scope = await store.initScope();
await store.put(quad, { scope });
await store.multiPut(quads, { scope });
await store.putStream(stream, { scope });
Quadstore.prototype.loadScope()
Each Scope
instance has an .id
property that acts as its unique identifier.
The loadScope()
method can be used to re-hydrate a scope through its .id
:
const scope = await store.initScope();
/* store scope.id somewhere */
/* read the previously-stored scope.id */
const scope = await store.loadScope(scopeId);
Quadstore.prototype.deleteScope()
Deletes all mappings of a given scope from the store.
const scope = await store.initScope();
/* ... */
await store.deleteScope(scope.id);
Quadstore.prototype.deleteAllScopes()
Deletes all mappings of all scopes from the store.
await store.deleteAllScopes();
SPARQL
SPARQL queries can be executed against a Quadstore
instance using any query
engine capable of querying across RDF/JS data sources.
An example of one such engine is quadstore-comunica, an engine built as a custom distribution and configuration of Comunica that implements the RDF/JS Query spec.:
Comunica is a knowledge graph querying framework. [...] Comunica is a meta query engine using which query engines can be created. It does this by providing a set of modules that can be wired together in a flexible manner. [...] Its primary goal is executing SPARQL queries over one or more interfaces.
In time, quadstore-comunica will be extended with custom query modules that will optimize query performance by pushing some matching and ordering operations down to quadstore itself.
import { MemoryLevel } from 'memory-level';
import { DataFactory } from 'rdf-data-factory';
import { Quadstore } from 'quadstore';
import { Engine } from 'quadstore-comunica';
const backend = new MemoryLevel();
const df = new DataFactory();
const store = new Quadstore({backend, dataFactory: df});
const engine = new Engine(store);
await store.open();
const bindingsStream = await engine.queryBindings('SELECT * {?s ?p ?o}');
More information on quadstore-comunica's repository.
Browser usage
The browser-level
backend for levelDB offers support for browser-side
persistent storage via IndexedDB.
quadstore
can be bundled for browser-side usage via Webpack, preferably using
version 5.x. The reference quadstore-browser is meant to help in getting
to a working Webpack configuration and also hosts a pre-built bundle with everything
that is required to use quadstore
in browsers.
Deno usage
quadstore
can be used with the Deno runtime via the skypack.dev
CDN:
import { DataFactory } from 'https://cdn.skypack.dev/[email protected]';
import { Quadstore } from 'https://cdn.skypack.dev/[email protected]';
import { MemoryLevel } from 'https://cdn.skypack.dev/[email protected]';
import { Engine } from 'https://cdn.skypack.dev/[email protected]';
const backend = new MemoryLevel();
const dataFactory = new DataFactory();
const store = new Quadstore({ backend, dataFactory });
const engine = new Engine(store);
await store.open();
await store.put(dataFactory.quad(
dataFactory.namedNode('ex://s'),
dataFactory.namedNode('ex://p'),
dataFactory.namedNode('ex://o'),
));
const stream = await engine.queryBindings('SELECT * WHERE { ?s ?p ?o }');
stream.on('data', (bindings) => console.log(bindings));
Example usage:
deno run quadstore-test.ts
Performance
Performance is evaluated at tracked at https://github.com/quadstorejs/quadstore-perf
LICENSE
MIT. See LICENSE.md.