--- description: 검증된 사용 후기를 확인하고 GraphDB 사용성, 특징, 가격, 장점과 단점에 대한 자세한 정보를 확인해보세요! 비슷한 경쟁 제품도 확인이 가능합니다. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: GraphDB 가격, 사용 후기, 평점 | 켑테라 Capterra --- Breadcrumb: [홈](/) > [데이터베이스 소프트웨어](/directory/18/database-management/software) > [GraphDB](/software/157533/graph-db) # GraphDB Canonical: https://www.capterra.co.kr/software/157533/graph-db Page: 1 / 2\ 다음: [Next page](https://www.capterra.co.kr/software/157533/graph-db?page=2) > Ontotext GraphDB를 사용하면 다양한 데이터를 연결하고, 시맨틱 검색을 위해 인덱스를 만들고, 텍스트 분석을 통해 데이터베이스를 강화하여 뛰어난 지식 그래프를 작성할 수 있습니다. > > Verdict: Rated **4.7/5** by 26 users. Top-rated for **추천 가능성**. ----- ## Overview ### GraphDB은(는) 누가 사용하나요? GraphDB는 의료 및 생명 과학, 금융 및 보험, 제조, 비즈니스 및 위험 인텔리전스, 미디어 및 STM 퍼블리셔, 과학, GLAM 부문의 사용 사례에 선호되는 RDF Tripletore입니다. ## Quick Stats & Ratings | Metric | Rating | Detail | | **종합** | **4.7/5** | 26 리뷰 | | 사용 편의성 | 4.6/5 | Based on overall reviews | | 고객 지원 | 4.5/5 | Based on overall reviews | | 비용 대비 가치 | 4.6/5 | Based on overall reviews | | 특징 | 4.5/5 | Based on overall reviews | | Recommendation percentage | 90% | (9/10 추천 가능성) | ## 공급업체 정보 - **회사**: Ontotext - **Location**: Sofia, 불가리아 - **Founded**: 2008 ## Commercial Context - **Pricing model**: (Free version available) (무료 체험판) - **Target Audience**: 자영업, 2~10, 11~50, 51~200, 201~500, 501~1,000, 1,001~5,000, 5,001~10,000, 10,000+ - **Deployment & Platforms**: 클라우드, SaaS, 웹 기반, Mac(데스크톱), Windows(데스크톱), Linux(데스크톱), Windows(온프레미스), Linux(온프레미스) - **Supported Languages**: 영어 - **Available Countries**: 가나, 가봉, 가이아나, 감비아, 건지, 과들루프, 과테말라, 괌, 그레나다, 그리스, 그린란드, 기니, 기니비사우, 나미비아, 나우루, 나이지리아, 남아프리카, 네덜란드, 네팔, 노르웨이 and 209 more ## 특징 - 검색/필터 - 그래프 데이터베이스 - 데이터 가져오기/내보내기 - 데이터 검색 - 데이터 동기화 - 데이터 복제 - 데이터 스토리지 관리 - 백업 및 복구 ## Integrations (1 total) - MongoDB ## Support Options - 이메일/지원 센터 - FAQ/포럼 - 지식 기반 - 전화 지원 - 채팅 ## Category - [데이터베이스 소프트웨어](https://www.capterra.co.kr/directory/18/database-management/software) ## 관련 범주 - [데이터베이스 소프트웨어](https://www.capterra.co.kr/directory/18/database-management/software) - [NoSQL 데이터베이스 소프트웨어](https://www.capterra.co.kr/directory/32257/nosql-databases/software) ## 대안 1. [Redis Enterprise](https://www.capterra.co.kr/software/173860/redis-enterprise) — 4.8/5 (65 reviews) 2. [Couchbase Server](https://www.capterra.co.kr/software/132494/couchbase-server) — 4.1/5 (12 reviews) ## 리뷰 ### "The best RDF graph database in the market" — 5.0/5 > **Stratos** | *2023년 12월 6일* | 정보 서비스 | Recommendation rating: 10.0/10 > > **장점**: - 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. > > **단점**: 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. > > 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. ----- ### "Nearly instantaneous, rich-featured semantic repository" — 5.0/5 > **Mark** | *2019년 10월 29일* | 리서치 | Recommendation rating: 10.0/10 > > **장점**: 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. > > **단점**: 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.) > > There are other triple stores with different feature sets, but it don't think there's any triplestore that is better than GraphDB. ----- ### "review of graphdb in the production planning" — 4.0/5 > **Alexander** | *2019년 11월 5일* | 리서치 | Recommendation rating: 6.0/10 > > **장점**: - 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 > > **단점**: - 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 > > We are currently using graphdb in a PoC as semantic web stack compliant database for data integration in a laboratory environment. ----- ### "GraphDB" — 5.0/5 > **Joop** | *2019년 11월 5일* | 정부 행정 | Recommendation rating: 8.0/10 > > **장점**: 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. > > **단점**: OntoRefine. It looks fine but we missed some modeling features. We switched back to OpenRefine. > > 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. ----- ### "One of the best for graph databases" — 4.0/5 > **검증된 리뷰어** | *2019년 10월 3일* | 리서치 | Recommendation rating: 8.0/10 > > **장점**: Sparql support. Ease of setup. Webservice api. Functionality of free version. > > **단점**: Speed changes after some updates. Removal from GCC > > 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. ----- Page: 1 / 2\ 다음: [Next page](https://www.capterra.co.kr/software/157533/graph-db?page=2) ## Links - [View on Capterra](https://www.capterra.co.kr/software/157533/graph-db) ## This page is available in the following languages | Locale | URL | | de | | | de-AT | | | de-CH | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-IL | | | en-IN | | | en-NZ | | | en-SG | | | en-ZA | | | es | | | es-AR | | | es-CL | | | es-CO | | | es-CR | | | es-DO | | | es-EC | | | es-MX | | | es-PA | | | es-PE | | | fr | | | fr-BE | | | fr-CA | | | fr-LU | | | it | | | ko | | | nl | | | nl-BE | | | pt | | | pt-PT | | ----- ## Structured Data