Search Results for "text graph"

XTDB is a general-purpose bitemporal database for SQL, Datalog & graph queries. XTDB contains a perfect, immutable record of every fact your system has ever known. See the entire history of your business, everywhere. Immutable records are incomplete without time-traveling queries. XTDB allows you to query the entire timeline. Make retroactive corrections, simplify data migrations, and get clarity on out-of-order events. It is the interconnection of facts that makes them valuable. Query the...

OrientDB is an Open Source Multi-Model NoSQL DBMS with the support of Native Graphs, Documents, Full-Text search, Reactivity, Geo-Spatial and Object Oriented concepts. It's written in Java and it's amazingly fast. No expensive run-time JOINs, connections are managed as persistent pointers between records. You can traverse thousands of records in no time. Supports schema-less, schema-full and schema-mixed modes. Has a strong security profiling system based on user, roles and predicate...

CRGREP searches for matching text in databases, various document formats, archives and other difficult to access resources. A command line tool for name and content text matching in database tables, plain files, MS Office documents, PDF, archives, MP3 audio, image meta-data, scanned documents, maven dependencies and web resources. CRGREP will search resources within resources of any arbitrary combination or depth, so text within a document within a zip archive, and so on. Here you...

"Information is data in action", and, consequently, having good quality data is essential. The AESTEL package contains two highly configurable applications for data management: A data loader and a reporting application, i.e. DataLoader and AEREA, respectively. The data loader application applies user-defined instructions to validate, process and load data. The reporting application provides a query builder and spreadsheet template designer. Both applications work with any relational data...

Wikipedia Concept Association Map (WCAM) is new approach for textual knowledge representation and understanding. All concepts and associations are stored in a graph database for better performance and easy distribution.