Download ZIP | Join us on Slack | Community Forum
Working on your first Pull Request? You can learn how from this free series How to Contribute to an Open Source Project on GitHub
SirixDB - An Evolutionary, Temporal NoSQL Document Store
Store and query revisions of your data efficiently
"Remember that you're lucky, even if you don't think you are, because there's always something that you can be thankful for." - Esther Grace Earl (http://tswgo.org)
Discuss it in the Community Forum
Why should you even bother? Advantages of a native, temporal database system
We could write quite a bunch of stuff, why it's often times of great value to keep past state of your data in a storage system, but recently we stumbled across an excellent blog post, which explains the advantages of keeping historical data very well. In a nutshell it's all about looking at the evolution of your data, finding trends, doing audits, implementing efficient undo-/redo-operations... the Wikipedia page has a bunch of examples. We recently also added use cases over here.
Our strong belief is, that a temporal storage system must address the issues, which arise from keeping past state way better than traditional approaches. Usually, storing time varying, temporal data in database systems, which do not support the storage thereof natively results in a lot of unwanted hurdle. Storage space is wasted, query performance to retrieve past states of your data is not ideal and usually temporal operations are missing altogether.
Data must be stored in a way, that storage space is used as effectively as possible while supporting the reconstruction of each revision, as it was seen by the database during the commits, in linear time, no matter if it's the very first revision or the most recent revision. Ideally query time of old/past revisions as well as the most recent revision should be in the same runtime complexity (logarithmic when querying for specific records).
We not only support snapshot based versioning on a record granular level through a novel versioning algorithm called sliding snapshot, but also time travel queries, efficient diffing between revisions and the storage of semi-structured data to name a few.
The following time-travel query to be executed on our binary JSON representation should give an initial impression of what's possible:
let $statuses := jn:open('mycol.jn','mydoc.jn', xs:dateTime('2019-04-13T16:24:27Z'))=>statuses
let $foundStatus := for $status in bit:array-values($statuses)
let $dateTimeCreated := xs:dateTime($status=>created_at)
where $dateTimeCreated > xs:dateTime("2018-02-01T00:00:00") and not(exists(jn:previous($status)))
order by $dateTimeCreated
return $status
return {"revision": sdb:revision($foundStatus), $foundStatus{text}}
The query basically opens a database/resource in a specific revision based on a timestamp (2019–04–13T16:24:27Z
) and searchs for all statuses, which have a created_at
timestamp, which has to be greater than the 1st of February in 2018 and did not exist in the previous revision. =>
is a dereferencing operator used to dereference keys in JSON objects, array values can be accessed as shown with the function bit:array-values or through specifying an index, starting with zero: array[[0]] for instance specifies the first value of the array.
Design goals
Sirix is designed with the following goals in mind:
- Concurrent
- Sirix contains very few locks and aims to be as suitable for multithreaded systems as possible.
- Asynchronous (REST API)
- Sirix is asynchronous: operations can happen independently; writes and
reads from the disk need not block. Each transaction is bound to a specific
revision and only ever one read/write-transaction on a resource can exist concurrently
to N read-only-transactions.
- Revision history
- Sirix stores a revision history of every resource in the database without imposing extra
overhead. This means that you can revert any revision into an earlier version,
backing up the system automatically and without imposed overhead from
copying, doing time travel queries to analyse the past / and or for auditing purposes, to correct humans- or application-errors... This is maybe the most important feature.
- Data integrity
- Sirix, like ZFS, stores full checksums of the pages in the parent pages. That means that almost all data corruption will be detected upon read in the future, once we replicate database pages.
- Copy-on-write semantics
- Similarly to the file systems Btrfs and ZFS, Sirix uses CoW semantics, meaning that no page
is ever overwritten directly, but instead it is copied and written to a new
location.
- Per revision and per record version / novel versioning approach
- Sirix not only versions on a per page-basis, but also on a per record basis. Thus, when a record in a page changed, not the whole page has to be duplicated. Instead, we implemented several versioning strategies known from backup systems and developed a novel strategy, to avoid read- or write-peaks.
- Guaranteed atomicity (without a WAL)
- The system will never enter an inconsistent state (unless there is hardware
failure), meaning that unexpected power-off won't ever damage the system. This is accomplished without the overhead of a write-ahead-log (WAL).
- Log-structured / SSD friendly
- Sirix never overrides data. It batches writes and synchs everything to a flash drive during a commit.
Versioning at the sub-file level / supporting time-travel queries
Sirix is a storage system, which brings versioning to a sub-file granular level while taking full advantage of flash based drives as for instance SSDs. As such per revision as well as per page deltas are stored. Time-complexity for retrieval of records/nodes and the storage are logarithmic (O(log n)). Space complexity is linear (O(n)). Currently, we provide several APIs which are layered. A very low level page-API, which handles the storage and retrieval of records on a per page-fragment level (whereas a buffer manager handles the caching of pages in-memory and the versioning takes place even on a lower layer for storing and reconstructing the page-fragments in CPU-friendly algorithms), a cursor based API to store and navigate through records (currently XML/XDM nodes) on top, a DOM-alike node layer for simple in-memory processing of these nodes, which is used by Brackit, a sophisticated XQuery processor. And last but not least a RESTful asynchronous HTTP-API. We provide a seamless integration of a native JSON layer besides the XML node layer, that is we extend the XQuery Data Model (XDM) with other node types (support for JSONiq like queries through the XQuery processor Brackit). In general, however we could store every kind of data. We provide
- The current revision of the resource or any subset thereof;
- The full revision history of the resource or any subset thereof;
- The full modification history of the resource or any subset thereof.
We not only support all XPath axis (as well as a few more like as for instance a PostOrderAxis) to query a resource in one revision but also novel temporal axis which facilitate navigation in time. A transaction (cursor) on a resource can be started either by specifying a specific revision number (to open a revision/version/snapshot of a resource) or by a given point in time. The latter starts a transaction on the revision number which was committed closest to the given timestamp.
Articles published on Medium:
Table of contents
Getting started
git clone https://github.com/sirixdb/sirix.git
or use the following dependencies in your Maven (or Gradle?) project.
We just changed to Java11 (OpenJDK 11).
Maven artifacts
At this stage of development you could use the latest SNAPSHOT artifacts from the OSS snapshot repository to get the most recent changes. However, we just released version 0.9.1 of Sirix :-)
Just add the following repository section to your POM file:
<repository>
<id>sonatype-nexus-snapshots</id>
<name>Sonatype Nexus Snapshots</name>
<url>https://oss.sonatype.org/content/repositories/snapshots</url>
<releases>
<enabled>false</enabled>
</releases>
<snapshots>
<enabled>true</enabled>
</snapshots>
</repository>
Note that we changed the groupId from com.github.sirixdb.sirix
to io.sirix
. Most recent version is 0.9.2-SNAPSHOT.
Maven artifacts are deployed to the central maven repository (however please use the SNAPSHOT-variants as of now). Currently the following artifacts are available:
Core project:
<dependency>
<groupId>io.sirix</groupId>
<artifactId>sirix-core</artifactId>
<version>0.9.2-SNAPSHOT</version>
</dependency>
Brackit binding:
<dependency>
<groupId>io.sirix</groupId>
<artifactId>sirix-xquery</artifactId>
<version>0.9.2-SNAPSHOT</version>
</dependency>
Asynchronous, RESTful API with Vert.x, Kotlin and Keycloak (the latter for authentication via OAuth2/OpenID-Connect):
<dependency>
<groupId>io.sirix</groupId>
<artifactId>sirix-rest-api</artifactId>
<version>0.9.2-SNAPSHOT</version>
</dependency>
Other modules are currently not available (namely the GUI, the distributed package as well as an outdated Saxon binding).
Docker images for the Sirix HTTP(S)-Server / the REST-API
First, we need a running Keycloak server for now on port 8080.
As a Keycloak instance is needed for the RESTful-API we'll build a simple docker compose file maybe with a demo database user and some roles in the future.
For running a keycloak docker container you could for instance use the following docker command:
docker run -d --name keycloak -p 8080:8080 -e KEYCLOAK_USER=admin -e KEYCLOAK_PASSWORD=admin -e KEYCLOAK_LOGLEVEL=DEBUG jboss/keycloak
. Afterwards it can be configured via a Web UI: http://localhost:8080. Keycloak is needed for our RESTful, asynchronous API. It is the authorization server instance.
Docker images of Sirix can be pulled from Docker Hub (sirixdb/sirix). However the easiest way for now is to download Sirix, then
- Change into the sirix-rest-api bundle:
cd bundles/sirix-rest-api
- Change the configuration in
src/main/resources/sirix-conf.json
and add the secret from Keycloak (see for instance this great tutorial and change the HTTP(S)-Server port Sirix is listening on:
- You can simply use the example
key.pem
/cert.pem
files in src/main/resources
for HTTPS (for example.org), but you have to change it, once we release the stable version for production. Then you for sure have to use a certificate/key for your domain. You could use Let's Encrypt for instance to get an SSL/TLS certificate for free. - Build the docker image:
docker build -t sirixdb/sirix
- Run the docker container:
docker run --network=host -t -i -p 9443:9443 sirixdb/sirix
(on Windows this does not seem to work)
Sirix should be up and running afterwards. Please let us know if you have any trouble setting it up.
Command line tool
We ship a (very) simple command line tool for the sirix-xquery bundle:
Get the latest sirix-xquery JAR with dependencies.
First steps
Please have a look into our sirix-example project how to use Sirix from Java or have a look into the documentation.
Documentation
We are currently working on the documentation. You may find first drafts and snippets in the documentation and in this README. Furthermore you are kindly invited to ask any question you might have (and you likely have many questions) in the community forum (preferred) or in the Slack channel.
Please also have a look at and play with our sirix-example bundle which is available via maven or our new asynchronous RESTful API (shown next).
The following sections show different APIs to interact with Sirix.
RESTful-API
We provide a simple, asynchronous RESTful-API. Authorization is done via OAuth2 (Password Credentials/Resource Owner Flow) using a Keycloak authorization server instance. Keycloak can be set up as described in this excellent tutorial.
All you have to change is setting the client-id to "sirix" and put the client secret into our configuration file. Change the value of "client.secret" to whatever Keycloak set up (can be found on the credetials tab of your account). Regarding Keycloak the direct access grant on the settings tab must be enabled. Our user-roles are "create" to allow creating databases/resources, "view" to allow to query database resources, "modify" to modify a database resource and "delete" to allow deletion thereof. Furthermore, a key.pem
and a cert.pem
file are needed. These two files have to be in your user home directory in a directory called "sirix-data", where Sirix stores the databases. For demo purposes they can be copied from our resources directory.
To created a fat-JAR. Download our ZIP-file for instance, then
cd bundles/sirix-rest-api
mvn clean package -DskipTests
And a fat-JAR with all required dependencies should have been created in your target folder.
Once also Keycloak is set up we can start the server via:
java -jar -Duser.home=/opt/intrexx sirix-rest-api-*-SNAPSHOT-fat.jar -conf sirix-conf.json -cp /opt/sirix/*
If you like to change your user home directory to /opt/sirix
for instance.
The fat-JAR in the future will be downloadable from the maven repository.
After Keycloak and our server are up and running, we can write a simple HTTP-Client. We first have to obtain a token from the /login
endpoint with a given "username/password" JSON-Object. Using an asynchronous HTTP-Client (from Vert.x) in Kotlin, it looks like this:
val server = "https://localhost:9443"
val credentials = json {
obj("username" to "testUser",
"password" to "testPass")
}
val response = client.postAbs("$server/login").sendJsonAwait(credentials)
if (200 == response.statusCode()) {
val user = response.bodyAsJsonObject()
val accessToken = user.getString("access_token")
}
This access token must then be sent in the Authorization HTTP-Header for each subsequent request. Storing a first resource would look like (simple HTTP PUT-Request):
val xml = """
<xml>
foo
<bar/>
</xml>
""".trimIndent()
var httpResponse = client.putAbs("$server/database/resource1").putHeader(HttpHeaders.AUTHORIZATION.toString(), "Bearer $accessToken").putHeader(HttpHeaders.CONTENT_TYPE.toString(), "application/xml").putHeader(HttpHeaders.ACCEPT.toString(), "application/xml").sendBufferAwait(Buffer.buffer(xml))
if (200 == response.statusCode()) {
println("Stored document.")
} else {
println("Something went wrong ${response.message}")
}
First, an empty database with the name database
with some metadata is created, second the XML-fragment is stored with the name resource1
. The PUT HTTP-Request is idempotent. Another PUT-Request with the same URL endpoint would just delete the former database and resource and create the database/resource again. Note that every request now has to contain an HTTP-Header
which content type it sends and which resource-type it expects (Content-Type: application/xml
and Accept: application/xml
) for instance. This is needed as we now support the storage of and retrieval of XML or JSON-data. The following sections show the API for usage with out binary and in-memory XML representation.
The HTTP-Response should be 200 and the HTTP-body yields:
<rest:sequence xmlns:rest="https://sirix.io/rest">
<rest:item>
<xml rest:id="1">
foo
<bar rest:id="3"/>
</xml>
</rest:item>
</rest:sequence>
We are serializing the generated IDs from our storage system for element-nodes.
Via a GET HTTP-Request
to https://localhost:9443/database/resource1
we are also able to retrieve the stored resource again.
However, this is not really interesting so far. We can update the resource via a POST-Request
. Assuming we retrieved the access token as before, we can simply do a POST-Request and use the information we gathered before about the node-IDs:
val xml = """
<test>
yikes
<bar/>
</test>
""".trimIndent()
val url = "$server/database/resource1?nodeId=3&insert=asFirstChild"
val httpResponse = client.postAbs(url).putHeader(HttpHeaders.AUTHORIZATION
.toString(), "Bearer $accessToken").putHeader(HttpHeaders.CONTENT_TYPE.toString(), "application/xml").putHeader(HttpHeaders.ACCEPT.toString(), "application/xml").sendBufferAwait(Buffer.buffer(xml))
The interesting part is the URL, we are using as the endpoint. We simply say, select the node with the ID 3, then insert the given XML-fragment as the first child. This yields the following serialized XML-document:
<rest:sequence xmlns:rest="https://sirix.io/rest">
<rest:item>
<xml rest:id="1">
foo
<bar rest:id="3">
<test rest:id="4">
yikes
<bar rest:id="6"/>
</test>
</bar>
</xml>
</rest:item>
</rest:sequence>
The interesting part is that every PUT- as well as POST-request does an implicit commit
of the underlying transaction. Thus, we are now able send the first GET-request for retrieving the contents of the whole resource again for instance through specifying an simple XPath-query, to select the root-node in all revisions GET https://localhost:9443/database/resource1?query=/xml/all-times::*
and get the following XPath-result:
<rest:sequence xmlns:rest="https://sirix.io/rest">
<rest:item rest:revision="1" rest:revisionTimestamp="2018-12-20T18:44:39.464Z">
<xml rest:id="1">
foo
<bar rest:id="3"/>
</xml>
</rest:item>
<rest:item rest:revision="2" rest:revisionTimestamp="2018-12-20T18:44:39.518Z">
<xml rest:id="1">
foo
<bar rest:id="3">
<xml rest:id="4">
foo
<bar rest:id="6"/>
</xml>
</bar>
</xml>
</rest:item>
</rest:sequence>
In general we support several additional temporal XPath axis:
future::
future-or-self::
past::
past-or-self::
previous::
previous-or-self::
next::
next-or-self::
first::
last::
all-time::
The same can be achieved through specifying a range of revisions to serialize (start- and end-revision parameters) in the GET-request:
GET https://localhost:9443/database/resource1?start-revision=1&end-revision=2
or via timestamps:
GET https://localhost:9443/database/resource1?start-revision-timestamp=2018-12-20T18:00:00&end-revision-timestamp=2018-12-20T19:00:00
We for sure are also able to delete the resource or any subtree thereof by an updating XQuery expression (which is not very RESTful) or with a simple DELETE
HTTP-request:
val url = "$server/database/resource1?nodeId=3"
val httpResponse = client.deleteAbs(url).putHeader(HttpHeaders.AUTHORIZATION
.toString(), "Bearer $accessToken").putHeader(HttpHeaders.ACCEPT.toString(), "application/xml").sendAwait()
if (200 == httpResponse.statusCode()) {
...
}
This deletes the node with ID 3 and in our case as it's an element node the whole subtree. For sure it's committed as revision 3 and as such all old revisions still can be queried for the whole subtree (or in the first revision it's only the element with the name "bar" without any subtree).
If we want to get a diff, currently in the form of an XQuery Update Statement (but we could serialize them in any format), simply call the XQuery function sdb:diff
:
sdb:diff($coll as xs:string, $res as xs:string, $rev1 as xs:int, $rev2 as xs:int) as xs:string
For instance via a GET-request like this for the database/resource we created above, we could make this request:
GET https://localhost:9443/?query=sdb%3Adiff%28%27database%27%2C%27resource1%27%2C1%2C2%29
Note that the query-String has to be URL-encoded, thus it's decoded
sdb:diff('database','resource1',1,2)
The output for the diff in our example is this XQuery-Update statement wrapped in an enclosing sequence-element:
<rest:sequence xmlns:rest="https://sirix.io/rest">
let $doc := sdb:doc('database','resource1', 1)
return (
insert nodes <xml>foo<bar/></xml> as first into sdb:select-node($doc, 3)
)
</rest:sequence>
This means the resource1
from database
is opened in the first revision. Then the subtree <xml>foo<bar/></xml>
is appended to the node with the stable node-ID 3 as a first child.
https://github.com/sirixdb/sirix/wiki/RESTful-API gives an overview about the API.
DOM alike API
Think of this rather low level API as a persistent (in the sense of storing it to disk/a flash drive) DOM interface for Sirix, whereas nodes can be selected by a transactional cursor API by their unique identifier, which has been created during insertion with a sequence generator. Another DOM like API is available through our XQuery layer, which adds a simple Interface for in-memory node instances. However the low level API, which we are describing below doesn't have to have all nodes in-memory (and it usually doesn't). Nodes are fetched from variable length pages which have been either cached by a buffer manager in memory or reside on the flash drive or a spinning disk and have to be read from a file.
var file = Paths.get("sirix-database");
var config = new DatabaseConfiguration(file);
Databases.createXmlDatabase(config);
try (var database = Databases.openXmlDatabase(file)) {
database.createResource(
ResourceConfiguration.newBuilder("resource")
.useDeweyIDs(true)
.useTextCompression(true)
.buildPathSummary(true)
.versioningApproach(Versioning.SLIDING_SNAPSHOT)
.build());
try (
var manager = database.openResourceManager("resource1");
var wtx = manager.beginNodeTrx()) {
wtx.insertSubtreeAsFirstChild(XMLShredder.createFileReader(LOCATION.resolve("input.xml")));
wtx.moveTo(2);
wtx.moveSubtreeToFirstChild(4)
final QName name = wtx.getName();
final String value = wtx.getValue();
wtx.commit();
wtx.insertElementAsFirstChild(new QName("foo"));
wtx.commit("[MOD] Inserted another element.");
final OutputStream out = new ByteArrayOutputStream();
new XmlSerializer.XmlSerializerBuilder(manager, out).prettyPrint().build().call();
System.out.println(out);
}
} catch (final SirixException | IOException | XMLStreamException e) {
}
There are N reading transactions as well as one write-transaction permitted on a resource.
A read-only transaction can be opened through:
var rtx = manager.beginNodeReadOnlyTrx()
The codè above starts a transaction on the most recent revision.
The following code starts a transaction at revision 1.
var rtx = manager.beginNodeReadOnlyTrx(1)
The next read only transaction is going to be stared on the revision, which has been committed at the closest timestamp to the given point in time.
var time = LocalDateTime.of(2018, Month.APRIL, 28, 23, 30);
var rtx = manager.beginNodeReadOnlyTrx(time.toInstant())
There are also several ways to start the single read/write-transaction:
XmlNodeTrx beginNodeTrx();
XmlNodeTrx beginNodeTrx(@Nonnegative int maxNodes);
XmlNodeTrx beginNodeTrx(TimeUnit timeUnit, int maxTime);
XmlNodeTrx beginNodeTrx(@Nonnegative int maxNodes, TimeUnit timeUnit, int maxTime);
With wtx.revertTo(int)
you're able to revert everything to an old revision (given by the integer). Followed by a commit the former version is commited as a new revision.
Use one of the provided axis to navigate through the DOM-like tree-structre (for instance in level order only through level 4):
var axis = new LevelOrderAxis.Builder(rtx).includeSelf().filterLevel(4).build()
Post-order traversal:
var axis = new PostOrderAxis(rtx)
And many more (for instance all XPath axis).
Or navigate to a specific node and then in time, for instance through all future revisions or all past revisions...:
var axis = new FutureAxis<XmlNodeReadTrx>(rtx)
var axis = new PastAxis<XmlNodeReadTrx>(rtx)
and many more as well.
Besides, we for instance provide diff-algorithms to import differences between several versions of (currently XML)-documents.
For instance after storing one revision in Sirix, we can import only the differences encountered by a sophisticated tree-to-tree diff-algorithm.
var resOldRev = Paths.get("sirix-resource-to-update");
var resNewRev = Paths.get("new-revision-as-xml-file");
FMSEImport.xmlDataImport(resOldRev, resNewRev);
Furthermore we provide diff-algorithms to determine all differences between any two revisions once they are stored in Sirix. To enable a fast diff-algorithm we optionally store a merkle-tree (that is each node stores an additional hash-value).
In order to invoke a diff you either use with a resource-manager and an immutable set of observers (2 and 1 are the revision numbers to compare):
DiffFactory.invokeFullDiff(
new DiffFactory.Builder(resourceMgr, 2, 1, DiffOptimized.HASHED, ImmutableSet.of(observer)))
Or you invoke a structural diff, which does not check attributes or namespace-nodes:
DiffFactory.invokeStructuralDiff(
new DiffFactory.Builder(resourceMgr, 2, 1, DiffOptimized.HASHED, ImmutableSet.of(observer)))
An observer simply has to implement this interface:
public interface DiffObserver {
void diffListener(@Nonnull DiffType diffType, long newNodeKey, long oldNodeKey,
@Nonnull DiffDepth depth);
void diffDone();
}
On top of this API we built a brackit(.org) binding, which enables XQuery support as well as another DOM-alike API with DBNode-instances (in-memory) nodes (for instance public DBNode getLastChild()
, public DBNode getFirstChild()
, public Stream<DBNode> getChildren()
...). You can also mix the APIs.
Simple XQuery Examples
Test if fragments of the resource are not present in the past. In this example they are appended to a node in the most recent revision and stored in a subsequent revision)
(* Loading document: *)
bit:load('mydoc.xml', '/tmp/sample8721713104854945959.xml')
(* Update loaded document: *)
let $doc := doc('mydoc.xml')
INSERT NODES <a><b/>test</a> INTO $doc/log
(* intermediate explicit commit *)
sdb:commit($doc)
(* Query loaded document: *)
doc('mydoc.xml')/log/all-time::*
(* First version: *)
<log tstamp="Fri Jun 14 07:59:08 CEST 2013" severity="low">
<src>192.168.203.49</src>
<msg>udic fyllwx abrjxa apvd</msg>
</log>
(* Second version: *)
<log tstamp="Fri Jun 14 07:59:08 CEST 2013" severity="low">
<src>192.168.203.49</src>
<msg>udic fyllwx abrjxa apvd</msg>
<a>
<b/>
test
</a>
</log>
(* Query loaded document (nodes, which are children of the log-element but did not exist in the past): *)
(* The second revision is initially loaded *)
doc('mydoc.xml', 2)/log/*[not(past::*)]
<a>
<b/>
test
</a>
Creation of a path index for all paths (note that we already can keep a path summary):
try (final DBStore store = DBStore.newBuilder().build()) {
final QueryContext ctx3 = new QueryContext(store);
final XQuery q = new XQuery(new SirixCompileChain(store),
"let $doc := sdb:doc('mydocs.col', 'resource1', (), fn:boolean(1)) "
+ "let $stats := sdb:create-path-index($doc, '//*') "
+ "return <rev>{sdb:commit($doc)}</rev>");
q.serialize(ctx3, System.out);
}
Temporal XPath axis extensions include:
future::
future-or-self::
past::
past-or-self::
previous::
previous-or-self::
next::
next-or-self::
first::
last::
all-time::
Many more examples of creating name indexes, content and structure indexes and how to query them can be found in the examples module.
Have a look into the wiki for examples regarding a lower level (really powerful) cursor based API to navigate/and or modify the tree structure or to navigate in time.
A lot of the ideas still stem from the Ph.D. thesis of Marc Kramis: Evolutionary Tree-Structured Storage: Concepts, Interfaces, and Applications
http://www.uni-konstanz.de/mmsp/pubsys/publishedFiles/Kramis2014.pdf
As well as from Sebastian Graft's work and thesis:
https://kops.uni-konstanz.de/handle/123456789/27250
Getting Help
Any questions or even consider to contribute or use Sirix? Use the Community Forum to ask questions. Any kind of question, may it be a API-question or enhancement proposal, questions regarding use-cases are welcome... Don't hesitate to ask questions or make suggestions for improvements. At the moment also API-related suggestions and critics are of utmost importance.
Join us on Slack
You may find us on Slack for quick questions.
Visualizations (built on top of the cursor-based transaction API)
The following diagram shows a screenshot of an interactive visualization, which depicts moves of single nodes or whole subtress through hierarchical edge bundling.
A screencast is available depicting the SunburstView and the TextView side by side:
http://www.youtube.com/watch?v=l9CXXBkl5vI
Currently, as we focused on various improvements in performance and features of the core storage system, the visualizations are a bit dated (and not working), but in the future we aim to bring them into the web (for instance using d3) instead of providing a standalone desktop GUI.
Why should you even bother?
Do you have to handle irregular data without knowing the schema before storing the data? You currently store this data in a relational DBMS? Maybe a tree-structured (XML or JSON) storage system much better suits your needs as it doesn't require a predefined schema before even knowing the structure of the data which has to be persisted.
Do you have to store a snapshot of this irregular data? Furthermore questions such as
- How do we store snapshots of time varying data effectively and efficiently?
- How do we know which data has been modified ever since a specified snapshot/revision?
- How do we store the differences between two XML documents? Is the storage system able to determine the differences itself?
- Which item has been sold the most during the last month/year?
- Which item has the most sold copies?
- Which items have been added?
- Which items have been deleted?
Sirix might be a good fit if you have to answer any of these questions as it stores data efficiently and effectively.
Furthermore Sirix handles the import of differences between a Sirix-resource and a new version thereof in the form of
an XML-document (soon JSON as well). Thus, an algorithm takes care of determining the differences and transforms
the stored resource into a new snapshot/revision/version, which is the same as the new XML document once
the newest revision is serialized (despite whitespace). Despite this, we also support the import of a series of snapshots of
temporal data, whereas the detection of the differences is completely up to Sirix. Specifying unique node-IDs to match pairs
of nodes is not required.
Once several (for instance at the very minimum two) versions of resources have been stored in Sirix it's possible to determine
the differences of subtrees or the whole resource/tree-structure.
Furthermore you are encouraged to navigate and query a Sirix resource not only in space but also in time.
Opening a specific version is possible with XQuery, the Java-API or a RESTful Web-Service. Serializing either a single version or a bunch of versions is also supported. Despite, future work includes the specification
of a delta-format.
In addition Sirix provides a very powerful axis-API and exposes each XPath-axis as well as all temporal axis (to navigate in time), a LevelOrderAxis, a PostorderAxis and a special DescendantVisitorAxis which is able to use a visitor, skip whole subtrees from traversal (might also depend on the depth), terminate the processing and to skip the traversal of sibling nodes. Furthermore all filters for instance to filter specific nodes, QNames, text-values and so on are exposed. In contrast to other XML database systems we also support the movement of whole subtrees, without having to delete and reinsert the subtree (which would also change unique node-IDs).
Furthermore it is easy to store other record-types as the built-in (XDM) types.
All index-structures are always kept up-to-date and versioned just as the data itself. A path summary stores reference-counters, that is how many nodes are stored on a specific path.
In contrast to some other approaches we also store path class records (PCR), that is the node-IDs of path summary nodes in the value indexes.
Furthermore in stark contrast to all other approaches the authors are aware of moves are supported, which preserve node-identity and aren't simple combinations of insert/delete-subtree operations. Instead only local changes take place. However with the path summary and other index-structures enabled the operation is likewise costly.
Features in a nutshell
- Transactional, versioned, typed user-defined index-structures, which are automatically updated once a transaction commits.
- Through XPath-axis extensions we support the navigation not only in space but also in time (future::, past::, first::, last::...). Furthermore we provide several temporal XQuery functions due to our integral versioning approach.
- An in memory path summary, which is persisted during a transaction commit and always kept up-to-date.
- Configurable versioning at the database level (full, incremental, differential and a new sliding snapshot algorithm which balances reads and writes without introducing write-peaks, which are usually generated during intermediate full dumps, which are usually written to).
- Log-structured sequential writes and random reads due to transactional copy-on-write (COW) semantics. This offers nice benefits as for instance no locking for concurrent reading-transactions and it takes full advantage of flash disks while avoiding their weaknesses.
- Complete isolation of currently N read-transactions and a single write-transaction per resource.
- The page-structure is heavily inspired by ZFS and therefore also forms a tree. We'll implement a similar merkle-tree and store hashes of each page in parent-pointers for integrity checks.
- Support of XQuery and XQuery Update due to a slightly modified version of brackit(.org).
- Moves are additionally supported.
- Automatic path-rewriting of descendant-axis to child-axis if appropriate.
- Import of differences between two XML-documents, that is after the first version of an XML-document is imported an algorithm tries to update the Sirix resource with a minimum of operations to change the first version into the new version.
- A fast ID-based diff-algorithm which is able to determine differences between any two versions of a resource stored in Sirix optionally taking hashes of a node into account.
- The number of children of a node, the number of descendants, a hash as well as an ORDPATH / DeweyID label which is compressed on disk to efficiently determine document order as well as to support other nice properties of hierarchical node labels is optionally stored with each node. Currently the number of children is always stored and the number of descendants is stored if hashing is enabled.
- Flexible backend.
- Optional encryption and/or compression of each page on disk.
Furthermore we aim to support an extended XDM in order to store JSON natively with additional node-types in Sirix. The implementation should be straight forward. Afterwards we'll explore how to efficiently distribute Sirix with Vert.x or directly via an Ignite or Hazelcast data grid.
Besides, the architecture for versioning data is not restricted to tree-structures by all means as demonstrated in the Ph.D. Thesis of Sebastian Graf (Sirix originated a few years ago as a fork of Treetank going back to its roots and focusing on the versioning of tree-structured data): http://nbn-resolving.de/urn:nbn:de:bsz:352-272505
Storing files natively is also on our agenda.
Developers
Developers which are eager to put forth the idea of a versioned, secure database system especially suitable, but not restricted to rooted trees (serialized form as XML/JSON) are always welcome. The idea is not only to support (and extend querying) as for instance via XQuery efficiently, but also to support other datamining tasks such as the comparison of hierarchical tree-structures.
More visualizations
Further information
Sirix was initially forked from Treetank (https://github.com/disy/treetank).
As such my deepest gratitude to all the other students who worked on the project.
First of all:
- Marc Kramis for his first drafts,
- Sebastian Graf for his almost complete rewrite of Treetank,
- Patrick Lang (RESTful API),
- Lukas Lewandowski (RESTful API),
- Tina Scherer (XPath engine)
and all the others who worked on the project.
License
This work is released under the BSD 3-clause license.
Involved People
Sirix is maintained by: