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Benchmarking

Write Performance Improves up to 500%

Evren Sirin

Feb 16, 2021

Stardog 7.5.0 improves write performance up to 500% in some cases. In this post I describe the details of this improvement and share detailed benchmarking results for update performance. Large Updates A common usage pattern for Stardog involves connecting to external data sources through virtual graphs that are queried on-demand without storing any data in Stardog. However, in some cases you might enable virtual graph caching to pull data into Stardog for indexing and in some other cases it is preferable or even necessary to materialize the data in Stardog completely.

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Stardog OAuth 2.0 Configuration

John Bresnahan

Feb 5, 2021

Stardog can be configured to use third party OAuth 2.0 identity providers for authentication. In this post we will explain how this is done and how to configure your Stardog server to do it. Architecture Proving Identity — Authentication When interacting with an Open Identify Connect service or an OAuth 2.0 indentity provider like Google the concept of a JSON Web Token (JWT) is at the center of the system.

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Benchmarking

Starbench and Dogfooding

Evren Sirin

Jan 27, 2021

Benchmarking is an essential part of developing any performance-sensitive software and Stardog is no exception. For a system as complex as Stardog, any single change in any part of the codebase might have unforeseen implications. Given that our customers have very different use cases, their data and query characteristics vary significantly making it harder for us to make sure their workloads will not slow down when we add a new feature or fix a bug.

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Volume Snapshots In Stardog

John Bresnahan

Jan 15, 2021

When running a datastore like Stardog it is important to take regular backups. However it is also important to consider the side effects that taking a backup can cause. Administrators have to balance the frequency of backups against the disruption to resources that can be caused creating that backup. If the backup process is CPU, memory, or IO intensive, care must be taken to make sure that it does not interrupt a period of heavy user activity.

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Introducing Plan Endpoint

Stanislav Klenin

Nov 12, 2020

When it comes to languages for querying databases, they tend to look more human-readable than a typical programming language. SPARQL, as well as SQL, employs declarative approach, allowing to describe what data needs to be retrieved without burdening the user with minutiae of how to do it. Besides being easier on the eyes, this leaves a DBMS free to choose the way it executes queries. And as is typical for database management systems, Stardog has its own internal representation for SPARQL queries: the query plan.

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Stardog Data Flow Automation with NiFi

Paul Jackson

Sep 10, 2020

We are happy to announce a new feature that enhances your ability to load data into Stardog’s graph database with the release of Nifi support in v7.4.

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Stored Query Service

Pavel Klinov

Aug 14, 2020

Stardog is a very extensible platform and the SERVICE keyword in SPARQL is one of its main extension points. It was originally introduced for SPARQL Federation, i.e. querying remote SPARQL endpoints on the Web, but at Stardog we recognised a long time ago that SERVICE could be used far beyond that. For us and our customers, it is a general mechanism for incorporating all sorts of computation within SPARQL queries, for example, we have been using it for full-text search and Machine Learning.

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5 Tips for Recruiting Startup Engineers

Evren Sirin

Aug 12, 2020

At Stardog I’m very lucky to work every day with the best engineers anyone could hope for. Startups are hard but having the right teammates makes all the difference when you are building an innovative product in a competitive market. Putting together a team that will tip the scale to your side is not easy. We have made some mistakes along the way with respect to recruiting. But as in any other aspect of running and growing a business, you need to learn from your mistakes and get better at it.

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Sandbox

Analyzing COVID-19 Data with SPARQL

Evren Sirin

Jul 13, 2020

For those of us living in the US, increasing COVID-19 case numbers across the country is unfortunately at the top of our minds. We do not lack access to data or infographics about the pandemic but having access to raw data and writing queries yourself can still give you different insights or at least get you better at writing queries. For this reason, we decided to turn the open-source COVID-19 dataset published by New York Times into RDF and included it in our publicly accessible Stardog Sandbox environment.

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Admin

Introducing Stardog Labs

Kendall Clark

Jul 6, 2020

I’m delighted to welcome you to Stardog Labs, a new hub of insight, news, and buzz about knowledge graph technology. The site will advance knowledge graph R&D by featuring technical blogs, showcasing job opportunities focused on knowledge graph development, and curating research papers and open source projects.

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CIM

Using CIM in Stardog

Evren Sirin

May 5, 2020

The Cloud Information Model (CIM) addresses the brittle data integrations that are common amongst enterprises. With the Stardog CIM archetype, you can start building your knowledge graph with a rich data model that is being standardized by industry leaders.

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Reasoning

Stream Reasoning With Stardog

Guest author Bram Steenwinckel

Mar 18, 2020

Guest author Bram Steenwinckel describes how to perform semantic reasoning over streaming data in your knowledge graph.

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The latest research

13th Annual International Technology, Education and Development Conference | Mar 28, 2019

Learning Analytics Software for Medical Students regarding Pregnancy Complications

The fast development of software for medicine caused the arise of new methods of learning about illnesses and complications which appear during pregnancies.

Carlos III University of Madrid | Oct 26, 2019

Formal ontologies and data shapes within the Software Engineering development lifecycle (TSE)

Business models, organizational activities and corporate strategies are now being reshaped to meet the new needs of a challenging and evolving environment in which more up-todate, secure, safer, cost-efficient and personalized software products and services must be timely delivered.

Lecture Notes in Computer Science | Nov 4, 2019

Evaluating Generalized Path Queries by Integrating Algebraic Path Problem Solving with Graph Pattern Matching

Path querying on Semantic Networks is gaining increased focus because of its broad applicability. Some graph databases offer support for variants of path queries e.g. shortest path.

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