GraphDB
von Ontotext
Wer verwendet GraphDB?
GraphDB ist die bevorzugte semantische Graph-Datenbank für Medienunternehmen, Verlage, Museen, Wissenschaft, Forschung im Bereich Gesundheitswesen und Biotechnologie, Versicherungen, Geschäfts- und Risikoanalysen, Marketingdienste.
Was ist GraphDB?
Graph DB ist eine semantische Graph-Datenbank, mit der Organisationen Inhalte in Form semantisch angereicherter intelligenter Daten speichern, organisieren und verwalten können. Graph DB umfasst Datenintegration und -verknüpfung, Einhaltung der W3C-Standards, ausdrucksstarkes, umfangreiches und flexibles Datenmodell, einen einzigen zusammenhängenden Informationsbereich, der aus strukturierten Daten und Textdokumenten besteht, Argumentation, verknüpfte Open-Data-Kompatibilität und Datenherkunft.
GraphDB – Details
Ontotext
http://www.ontotext.com/
Gegründet 2008
GraphDB – Preisübersicht
GraphDB bietet eine Gratisversion und eine kostenlose Testversion. Weitere Preisinformationen für GraphDB findest du unten.
Kostenlose Version
Ja
Gratis Testen
Ja
Einsatz
Installiert - Mac
Cloud, SaaS, Web
Installiert - Windows
Training
Persönlich
Live Online
Webinare
Dokumentation
Kundenbetreuung
Support während der Geschäftszeiten
Online
GraphDB Funktionen
Beliebte Produkte
GraphDB – Nutzerbewertungen
Zeigt 5 von 24 Nutzerbewertungen
Peter C.
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Overall Rating5/5
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Benutzerfreundlichkeit4/5
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Eigenschaften & Funktionalitäten5/5
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Kundenbetreuung5/5
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Preis-Leistungs-Verhältnis3/5
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Likelihood to Recommend
- Quelle des Nutzers
- Bewertet am 6.3.2018
"Very easy to use. Great support."
Kommentare: Ease of use.
Vorteile: Very easy to use when trying to parse through qualitative data for my dissertation. Needed to code data from multiple reflections and interviews.
Nachteile: was very easy to use.. took a little while to get up to speed, but once I did, I found it very intuitive and easy to use.
- Quelle des Nutzers
- Bewertet am 6.3.2018
Mark M.
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Overall Rating5/5
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Benutzerfreundlichkeit5/5
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Eigenschaften & Funktionalitäten4/5
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Kundenbetreuung5/5
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Preis-Leistungs-Verhältnis5/5
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Likelihood to Recommend
- Quelle des Nutzers
- Bewertet am 29.10.2019
"Nearly instantaneous, rich-featured semantic repository"
Kommentare: There are other triple stores with different feature sets, but it don't think there's any triplestore that is better than GraphDB.
Vorteile: It's very quick and easy to deploy GraphDB, ingest some RDF data, build queries in a IDE-like environment, and visualize relationships. A semantic similarity search tool is provided.
Nachteile: The OntoRefine tool is great for converting tabular data files into semantic triples, but there's no support for reading from relational databases. There are nice free text indexing & search tools, but no natural language parser for discovering entities and relationships. There are several pre-configured reasoning levels plus support for writing one's own rules, but no support for SWRL. Like most triplesotres, OWL2 reasoning over complex axioms and millions of data triples isn't fun/fast/realistic? (I say that based on a single node, two threads, and 256 GB RAM.)
Antwort des Softwareanbieters
von Ontotext an 4.11.2019
Thank you for your feedback, dear Mark! We will address all the recommendations you have left to the production team. Be well
- Quelle des Nutzers
- Bewertet am 29.10.2019
Joop V.
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Overall Rating5/5
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Benutzerfreundlichkeit5/5
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Eigenschaften & Funktionalitäten4/5
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KundenbetreuungUnrated
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Preis-Leistungs-Verhältnis5/5
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Likelihood to Recommend
- Quelle des Nutzers
- Bewertet am 5.11.2019
"GraphDB"
Kommentare:
We use GraphDB together with PoolParty as part of the Semantic Integrator solution.
We use GraphDB as our test triple store.
We use GraphDB to publish our "small" linked open data sets.
Vorteile:
I can be very short about my (our) experiences so far with GraphDB.
GraphDB is a clear winner for our usecases now. The learning curve is not steep, almost self-explanatory. It’s fast and it fits our needs; for now. We loved the graphics of GraphDB.
Nachteile: OntoRefine. It looks fine but we missed some modeling features. We switched back to OpenRefine.
Antwort des Softwareanbieters
von Ontotext an 11.11.2019
Thank you for your feedback, Joop. Be well!
- Quelle des Nutzers
- Bewertet am 5.11.2019
Alexander R.
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Overall Rating4/5
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Benutzerfreundlichkeit4/5
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Eigenschaften & Funktionalitäten3/5
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KundenbetreuungUnrated
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Preis-Leistungs-VerhältnisUnrated
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Likelihood to Recommend
- Quelle des Nutzers
- Bewertet am 5.11.2019
"review of graphdb in the production planning"
Kommentare: We are currently using graphdb in a PoC as semantic web stack compliant database for data integration in a laboratory environment.
Vorteile:
- ease of use (compared to other semantic web stack solutions)
- degree of inferencing implementation
- solution for transforming relational data into RDF with OpenRefine integration
- query performance (for SELECT, a evaluation for INSERT queries could not be given due to use of free version)
- good support even at free version
Nachteile:
- versioning of data (see changes over time)
- better controllability of role and rights (give rights for specific graphs in repository)
- no IdP based authentiaction like OpenID Connect (or something based on oAuth2 or at least SAML)
- easy to use integration for object storage (like AWS S3)
- documentation could be more detailed in some places
Antwort des Softwareanbieters
von Ontotext an 6.11.2019
Thank you for your feedback!
- Quelle des Nutzers
- Bewertet am 5.11.2019
Adonay andres A.
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Overall Rating5/5
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Benutzerfreundlichkeit5/5
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Eigenschaften & Funktionalitäten5/5
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Kundenbetreuung5/5
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Preis-Leistungs-Verhältnis5/5
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Likelihood to Recommend
- Quelle des Nutzers
- Bewertet am 29.10.2019
"The best Ontological Database Engine"
Kommentare: We've had a really good time working with it. Once we have a good model definition (which applies for any graph engine) it simply works and works really well.
Vorteile:
Over the last years, GraphDB has improved a lot, speaking about performance and inference. Graph DBs have always had the problem of being too slow for solving queries, we always had to structure them in a way that it was optimal for the engine to solve them. Graph DB has been always the most performant one.
Another feature that I loved from it is that, in order to install it, you simply copy a single jar file and you're almost ready to go. The user interface helps a lot. And its compliance with several standards for the interchange formats makes the way pretty straight forward no matter what tool was used to generate an interchange file.
Nachteile: The con I find with the product is about updates. When a new version comes up (which sometimes I don't know about the fact that there's a new release), I need to manually download it and deploy it. Also it would be desirable if we had access to connectors for different platforms. We work a lot with node.js and there's almost no libraries to use it with graphDB that are backed by ontotext.
Antwort des Softwareanbieters
von Ontotext an 4.11.2019
Dear Adonay, thank you for your great feedback! It is always great to see some extended prons and cons of the product you create! Regarding the cons: If you are part of the GraphDB Update announcements list you should receive a note about every update of GraphDB, so you won't be missing anything new. About the connectors: Latest releases of GraphDB support connectors and plugins to MongoDB Lucene, SOLR, Elasticsearch. If you need connectors to other popular services, you should make a request to the GraphDB Production team. Best Regards
- Quelle des Nutzers
- Bewertet am 29.10.2019
