Stores small-sized, immutable snapshots of your data and facilitates querying the full history
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"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)
SirixDB uses a huge persistent (in the functional sense) tree of tries, wherein the committed snapshots share unchanged pages and even common records in changed pages. The system only stores page-fragments instead of full pages during a commit to reduce write-amplification. During read operations, the system reads the page-fragments in parallel to reconstruct an in-memory page.
SirixDB currently supports the storage and (time travel) querying of both XML - and JSON-data in our binary encoding, tailored to support versioning. The index-structures and the whole storage engine has been written from scratch to support versioning natively. We might also implement the storage and querying of other data formats as relational data.
Note: Work on a Frontend built with Svelte, D3.js, and Typescript has just begun
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- Keeping All Versions of Your Data By Sharing Structure
- SirixDB Features
- Getting Started
- Getting Help
- Contributors
- License
We could write quite a bunch of stuff, why it's often of great value to keep all states of your data in a storage system. Still, 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 firm belief is that a temporal storage system must address the issues, which arise from keeping past states way better than traditional approaches. Usually, storing time-varying, temporal data in database systems that do not support the storage thereof natively results in many unwanted hurdles. They waste storage space, query performance to retrieve past states of your data is not ideal, and usually, temporal operations are missing altogether.
The DBS must store data in a way that storage space is used as effectively as possible while supporting the reconstruction of each revision, as the database saw it during the commits. All this should be handled in linear time, whether it's the first revision or the most recent revision. Ideally, query time of old/past revisions and the most recent revision should be in the same runtime complexity (logarithmic when querying for specific records).
SirixDB not only supports 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.
Executing the following time-travel query to on our binary JSON representation of Twitter sample data gives an initial impression of the possibilities:
let $statuses := jn:open('mycol.jn','mydoc.jn', xs:dateTime('2019-04-13T16:24:27Z'))=>statuses
let $foundStatus := for $status in $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 opens a database/resource in a specific revision based on a timestamp (2019–04–13T16:24:27Z
) and searches 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.
SirixDB is a log-structured, temporal NoSQL document store, which stores evolutionary data. It never overwrites any data on-disk. Thus, we're able to restore and query the full revision history of a resource in the database.
Some of the most important core principles and design goals are:
- Embeddable
- Similar to SQLite and DucksDB SirixDB is embeddable at its core. Other APIs as the non-blocking REST-API are built on top.
- Minimize Storage Overhead
- SirixDB shares unchanged data pages as well as records between revisions, depending on a chosen versioning algorithm during the initial bootstrapping of a resource. SirixDB aims to balance read and writer performance in its default configuration.
- Concurrent
- SirixDB contains very few locks and aims to be as suitable for multithreaded systems as possible.
- Asynchronous
- Operations can happen independently; each transaction is bound to a specific revision and only one read/write-transaction on a resource is permitted concurrently to N read-only-transactions.
- Versioning/Revision history
- SirixDB stores a revision history of every resource in the database without imposing extra overhead. It uses a huge persistent, durable page-tree for indexing revisions and data.
- Data integrity
- SirixDB, like ZFS, stores full checksums of the pages in the parent pages. That means that almost all data corruption can be detected upon reading in the future, we aim to partition and replicate databases in the future.
- Copy-on-write semantics
- Similarly to the file systems Btrfs and ZFS, SirixDB uses CoW semantics, meaning that SirixDB never overwrites data. Instead, database-page fragments are copied/written to a new location.
- Per revision and page versioning
- SirixDB does not only version on a per revision, but also on a per page-base. Thus, whenever we change a potentially small fraction of records in a data-page, it does not have to copy the whole page and write it to a new location on a disk or flash drive. Instead, we can specify one of several versioning strategies known from backup systems or a novel sliding snapshot algorithm during the creation of a database resource. The versioning-type we specify is used by SirixDB to version data-pages.
- Guaranteed atomicity and consistency (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 and SSD friendly
- SirixDB batches writes and syncs everything sequentially to a flash drive during commits. It never overwrites committed data.
Keeping the revision history is one of the main features in SirixDB. You can revert any revision into an earlier version or back up the system automatically without the overhead of copying. SirixDB only ever copies changed database-pages and, depending on the versioning algorithm you chose during the creation of a database/resource, only page-fragments, and ancestor index-pages to create a new revision.
You can reconstruct every revision in O(n), where n denotes the number of nodes in the revision. Binary search is used on an in-memory (linked) map to load the revision, thus finding the revision root page has an asymptotic runtime complexity of O(log n), where n, in this case, is the number of stored revisions.
Currently, SirixDB offers two built-in native data models, namely a binary XML store and a JSON store.
Articles published on Medium:
- Asynchronous, Temporal REST With Vert.x, Keycloak and Kotlin Coroutines
- Pushing Database Versioning to Its Limits by Means of a Novel Sliding Snapshot Algorithm and Efficient Time Travel Queries
- How we built an asynchronous, temporal RESTful API based on Vert.x, Keycloak and Kotlin/Coroutines for Sirix.io (Open Source)
- Why Copy-on-Write Semantics and Node-Level-Versioning are Key to Efficient Snapshots
Download ZIP or Git Clone
git clone https://github.com/sirixdb/sirix.git
or use the following dependencies in your Maven or Gradle project.
SirixDB uses Java15, thus you need an up-to-date Gradle (if you want to work on SirixDB) and IntelliJ or Eclipse.
At this stage of development, you should use the latest SNAPSHOT artifacts from the OSS snapshot repository to get the most recent changes.
Just add the following repository section to your POM or build.gradle 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>
repository {
maven {
url "https://oss.sonatype.org/content/repositories/snapshots/"
mavenContent {
snapshotsOnly()
}
}
}
Note that we changed the groupId from com.github.sirixdb.sirix
to io.sirix
. Most recent version is 0.9.6-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>0.9.6-SNAPSHOT</version>
</dependency>
compile group:'io.sirix', name:'sirix-core', version:'0.9.6-SNAPSHOT'
Brackit binding:
<dependency>
<groupId>io.sirix</groupId>
<artifactId>sirix-xquery</artifactId>
<version>0.9.6-SNAPSHOT</version>
</dependency>
compile group:'io.sirix', name:'sirix-xquery', version:'0.9.6-SNAPSHOT'
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>0.9.4-SNAPSHOT</version>
</dependency>
compile group: 'io.sirix', name: 'sirix-rest-api', version: '0.9.6-SNAPSHOT'
Other modules are currently not available (namely the GUI, the distributed package as well as an outdated Saxon binding).
The REST-API is asynchronous at its very core. We use Vert.x, which is a toolkit built on top of Netty. It is heavily inspired by Node.js but for the JVM. As such, it uses event loop(s), which is thread(s), which never should by blocked by long-running CPU tasks or disk-bound I/O. We are using Kotlin with coroutines to keep the code simple. SirixDB uses OAuth2 (Password Credentials/Resource Owner Flow) using a Keycloak authorization server instance.
For setting up the SirixDB HTTP-Server and a basic Keycloak-instance with a test realm:
git clone https://github.com/sirixdb/sirix.git
sudo docker-compose up keycloak
You can set up Keycloak as described in this excellent tutorial. Our docker-compose file imports a sirix realm with a default admin user with all available roles assigned. You can skip steps 3 - 7 and 10, 11, and simply recreate a client-secret
and change oAuthFlowType
to "PASSWORD". If you want to run or modify the integration tests, the client secret must not be changed. Make sure to delete the line "build: ." in the docker-compse.yml
file for the server image if you want to use the Docker Hub image.
- Open your browser. URL: http://localhost:8080
- Login with username "admin", password "admin"
- Create a new realm with the name "sirixdb"
- Go to
Clients
=>account
- Change client-id to "sirix"
- Make sure
access-type
is set toconfidential
- Go to
Credentials
tab - Put the
client secret
into the SirixDB HTTP-Server configuration file. Change the value of "client.secret" to whatever Keycloak set up. - If "oAuthFlowType" is specified in the ame configuration file change the value to "PASSWORD" (if not default is "PASSWORD").
- Regarding Keycloak the
direct access
grant on the settings tab must beenabled
. - Our (user-/group-)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. You can also assign
${databaseName}-
prefixed roles.
The following command will start the docker container
sudo docker-compose up
To created a fat-JAR. Download our ZIP-file for instance, then
cd bundles/sirix-rest-api
gradle build -x test
And a fat-JAR with all required dependencies should have been created in your target folder.
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.
Once also Keycloak is set up we can start the server via:
java -jar -Duser.home=/opt/sirix 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.
In order to run the integration tests under bundles/sirix-rest-api/src/test/kotlin
make sure that you assign your admin user all the user-roles you have created in the Keycloak setup (last step). Make sure that Keycloak is running first and execute the tests in your favorite IDE for instance.
Note that the following VM-parameters currently are needed: -ea --enable-preview --add-modules=jdk.incubator.foreign
We ship a (very) simple command-line tool for the sirix-xquery bundle:
Get the latest sirix-xquery JAR with dependencies.
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).
If you have any questions or are considering to contribute or use Sirix, please use the Community Forum to ask questions. Any kind of question, may it be an 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.
You may find us on Slack for quick questions.
SirixDB is maintained by
- Johannes Lichtenberger
And the Open Source Community.
As the project was forked from a university project called Treetank, my deepest gratitude to Marc Kramis, who came up with the idea of building a versioned, secure and energy-efficient data store, which retains the history of resources of his Ph.D. Furthermore, Sebastian Graf came up with a lot of ideas and greatly improved the implementation for his Ph.D. Besides, a lot of students worked and improved the project considerably.
Thanks goes to these wonderful people, who greatly improved SirixDB lately. SirixDB couldn't exist without the help of the Open Source community:
Contributions of any kind are highly welcome!
This work is released under the BSD 3-clause license.