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GraphDB
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.
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.
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Bewertungen über GraphDB
The best RDF graph database in the market
Kommentare: I have been using GraphDB for several years now and in almost all the positions I have worked for. In my opinion, it is by far the best tool out there for managing RDF graph databases. I love the simplicity of the interface, the practicality and aesthetic superiority of the visualizations and the overal "smoothness" that comes with using it. I cannot stress enough how great the technical support has always been at responding blazingly fast and always providing solutions to various issues one may come accross, even if they are GraphDB Free users.
Vorteile:
- Compliance to all the W3C standards, including SHACL. - User-friendly UI. - Aesthetically superior visualizations. - Great documentation: As detailed as it needs to be, but not more than that. - Great technical support (even for the GraphDB Free version users) that responds almost immediately.
Nachteile:
I honestly cannot think of anything negative to say about the tool and the customer support. Even though the company behind the tool (Ontotext) is a big global enterprise, every interaction I have with them feels like they genuinely care about whatever issues I am having with GraphDB and honestly want to help out in resolving it.
In Betracht gezogene Alternativen:
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 von Ontotext
vor 5 Jahren
Thank you for your feedback, dear Mark! We will address all the recommendations you have left to the production team. Be well
In Betracht gezogene Alternativen:
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 von Ontotext
vor 5 Jahren
Thank you for your feedback!
In Betracht gezogene Alternativen:
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 von Ontotext
vor 5 Jahren
Thank you for your feedback, Joop. Be well!
One of the best for graph databases
Kommentare:
The use of graphDB solves many speed issues as it is very fast.
The webservice api allows manipulation of the repositories (create, delete, import).
The only problem is that after some updates, the speed of the endpoint queries dorps very much.
An example for this if the migration from v8.11.1 to v9.0.
I am using the free version but in a single thread and they mention that the only limitation of the free version is the limitation of simultaneous queries to only two.
I had the same problems when i tried the enterprise edition for a trial period and never managed to reach the speed of the free version with any change I tried in the setup or options.
Vorteile:
Sparql support. Ease of setup. Webservice api. Functionality of free version.
Nachteile:
Speed changes after some updates. Removal from GCC
Antwort von Ontotext
vor 5 Jahren
Hi and thank you for your honest review. We want to help you solve all that bothers you when using GraphDB. Gould you write to our GraphDB Support team to investigate your problem with the speed. Please email them to graphdb-support@ontotext.com My colleagues will take care of you further. Be well, Regards, Milen
