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Blazegraph(tm) | Blazegraph(tm) is a scale-out storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates.

Blazegraph(tm) is a scale-out storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates. SPARQL UPDATE performance gain. An easy win with the right data structure. We had reports of a performance slowdown for SPARQL UPDATE INSERT/DELETE WHERE queries:. DELETE {.} INSERT {.} WHERE {.}. For example, you can observe this using the following SPARQL UPDATE request against a data set with 100k or more instances of rdf:label. O } INSERT {? O } WHERE {?

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Blazegraph(tm) | Blazegraph(tm) is a scale-out storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates. | blog.blazegraph.com Reviews

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Blazegraph(tm) is a scale-out storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates. SPARQL UPDATE performance gain. An easy win with the right data structure. We had reports of a performance slowdown for SPARQL UPDATE INSERT/DELETE WHERE queries:. DELETE {.} INSERT {.} WHERE {.}. For example, you can observe this using the following SPARQL UPDATE request against a data set with 100k or more instances of rdf:label. O } INSERT {? O } WHERE {?

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Blazegraph(tm) | Blazegraph(tm) is a scale-out storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates. | blog.blazegraph.com Reviews

https://blog.blazegraph.com

Blazegraph(tm) is a scale-out storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates. SPARQL UPDATE performance gain. An easy win with the right data structure. We had reports of a performance slowdown for SPARQL UPDATE INSERT/DELETE WHERE queries:. DELETE {.} INSERT {.} WHERE {.}. For example, you can observe this using the following SPARQL UPDATE request against a data set with 100k or more instances of rdf:label. O } INSERT {? O } WHERE {?

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blazegraph.com

Learn More About Blazegraph

https://www.blazegraph.com/learn

Embedded and Single Server. High Availability (HA) and Scale-Out. There’s lot’s of ways to learn more about Blazegraph. The public code samples to get started with an embedded application. Our user’s guide and wiki. Read out case studies. Leave a Reply Cancel reply. Your email address will not be published. Required fields are marked *. Sign up for the latest Blazegraph news! Sign up for the latest Blazegraph news! Blazegraph 2.1.4 Release. August 29, 2016. Blazegraph 2.1.2 Release. June 18, 2016.

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Blazegraph Video - in Press, Conferences & Webinars

https://www.blazegraph.com/learn/videos

Embedded and Single Server. High Availability (HA) and Scale-Out. Have you seen Blazegraph in the press, at conferences, or in webinars? Blazegraph at Super Computing 2015. Watch SYSTAP CEO Brad Bebee discuss Blazegraph DASL and GPU in the NVIDIA Booth at Super Computing 2015. Blazegraph Competes as one of 12 finalists for the Early Stage Challenge at the 2015 NVIDIA GPU Technology Conference. The Perfect Fit for Scalable Graph for Big Data. NYC Database Week March 2015. See Syapse Founder and President ...

blazegraph.com

Blazegraph Support Applications and Available Plans

https://www.blazegraph.com/product/support

Embedded and Single Server. High Availability (HA) and Scale-Out. To get started with Blazegraph, download. It and checkout out our quick start guide. There is a discount for start-ups, non-profits, universities, and research applications (See below). Startups are defined as companies with less than 20 employees and a maximum amount of $2M in annual revenue or funding. Contact us. If you have any questions about whether you qualify. 365 Days - Free). 7, 90, 180 or 365 days. 7 Days $750.00 USD. Startups a...

blazegraph.com

Blazegraph Licensing Enterprise Licensing

https://www.blazegraph.com/services/blazegraph-licensing

Embedded and Single Server. High Availability (HA) and Scale-Out. Blazegraph is freely available under the GPLv2. Open-source license. GPLv2 is a copyleft. If you have any questions about whether you qualify. We provide development and production support options for both open source and commercial licenses. We also offer Enterprise and OEM licensing. Please see our Support. Page to purchase support for production, development, or benchmarking. You can also contact us. Startups, Non-profits, and Research.

wiki.blazegraph.com

Concepts - Blazegraph

https://wiki.blazegraph.com/wiki/index.php/Concepts

SOLR External Full Text Search. SPARQL Tips and Tricks. Notes on compliance with the Sesame API. Using Blueprints with Blazegraph. Using Bigdata with the OpenRDF Sesame HTTP Server. Sesame API embedded mode. Sesame API remote mode. Blueprints API embedded mode. Blueprints API remote mode. Cluster Setup Guide Fedora 10. Cluster Setup Guide CentOS 5.3/5.4. External Full Text Search. Inference and Truth Maintenance. Rebuilding the Text Index. Graphs, RDF, And Blazegraph. RDF, RDFS and OWL. Is a formal speci...

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Blazegraph - Scalable Solutions, HA, Scale-out and GPU Acceleration

https://www.blazegraph.com/download

Embedded and Single Server. High Availability (HA) and Scale-Out. With Blazegraph is easier than ever. You can choose an executable jar, war file, or tar.gz distribution. Starting in 2.0.0, we also have a Debian and RPM deployer. For more download options, click here. Or higher is required to run Blazegraph. Blazegraph supports an executable jar deployment for getting started quickly. Download the jar and then simply point your browser at http:/ localhost:9999/blazegraph/. Blazegraph 2.1.4 Release.

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Developer Resources - Contributor Agreements (CA

https://www.blazegraph.com/develop

Embedded and Single Server. High Availability (HA) and Scale-Out. We are always looking for people with a background in graph databases and the semantic web and a passion for open source. If you are interested in being a contributor to the blazegraph open source project and joining our growing community please contact us. Sign up for the latest Blazegraph news! Blazegraph GPU uses acceleration for both graph query and very large scale graph analytics. Billions of edges in milliseconds. August 29, 2016.

blazegraph.com

Blazegraph Services by SYSTAP

https://www.blazegraph.com/services

Embedded and Single Server. High Availability (HA) and Scale-Out. Blazegraph Services by SYSTAP. Commercial Licensing: Commercial licensing is available directly. Or bundled with a support subscription. Developer Support Subscriptions: The best way to engage with our team of experts on using Blazegraph for your application. Production Support Subscriptions: The best way to provide productions support for your application powered by Blazegraph. Page for the current pricing or contact-us. August 29, 2016.

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Blazegraph Products

https://www.blazegraph.com/product

Embedded and Single Server. High Availability (HA) and Scale-Out. Blazegraph is ultra-scalable, high-performance graph database with support for the Blueprints and RDF/SPARQL APIs. Blazegraph is available in a range of versions that provide solutions to the challenge of scaling graphs. Blazegraph solutions range from millions to trillions of edges in the graph. Single Server and Embedded. High Availability and Scale Out. You can purchase support. For in-depth technical details see our Wiki. Blazegraph is...

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blog.blazegraph.com

Blazegraph(tm) | Blazegraph(tm) is a scale-out storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates.

Blazegraph(tm) is a scale-out storage and computing fabric supporting optional transactions, very high concurrency, and very high aggregate IO rates. SPARQL UPDATE performance gain. An easy win with the right data structure. We had reports of a performance slowdown for SPARQL UPDATE INSERT/DELETE WHERE queries:. DELETE {.} INSERT {.} WHERE {.}. For example, you can observe this using the following SPARQL UPDATE request against a data set with 100k or more instances of rdf:label. O } INSERT {? O } WHERE {?

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Thursday, 18 June 2015. Substituting registered container components for testing. I want to test my services end-to-end. I want to guarantee I'm testing behaviour and not implementation. I do not want my tests to be brittle and I want to refactor. I want to test that my container registration conventions. How do I substitute container components already registered by convention with my in-memory implementations? Without making changes to the production code? Here is an example, whereby a bootstrapped.