Database Revolution; Future of Information Publishing
In computing, extract, transform, and load (ETL) refers to a process in database usage and especially in data warehousing that: Extracts data from outside sourcesTransforms it to fit operational needs, which can include quality levelsLoads it into the end target (database, more specifically, operational data store, data mart, or data warehouse) ETL systems are commonly used to integrate data from multiple applications, typically developed and supported by different vendors or hosted on separate computer hardware. The disparate systems containing the original data are frequently managed and operated by different employees. For example a cost accounting system may combine data from payroll, sales and purchasing. Extract, transform, load
0830 - Cypher and Neo4j on Vimeo
NOTE: This post is quite outdated, stuff has changed since i wrote this. While you can somewhat safely ignore the alterations for increased address space of entities, the Property store has changed in a fundamental way. Neo4j Internals: File Storage
Atomic Wiki Higher-order functions are probably the most notable addition to the XQuery language in version 3.0 of the specification .
Using A Graph Database To Power The “Web of Things” Bio
PyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data. You can download PyTables and use it for free. You can access documentation, some examples of use and presentations in the HowToUse section. PyTables is built on top of the HDF5 library, using the Python language and the NumPy package. Getting the most *out* of your data
AllegroGraph News August 2011
high-performance graph database, data deduplication and bibliographic exploration Download latest release The version you will use with the evaluation license we provide here has the following configuration: SMALL size 1 session DEXHA disabled
orient - NoSQL document database light, portable and fast. Supports ACID Tx, Indexes, asynch queries, SQL layer, clustering, etc
A Graph Database
The context data model combines features of all the above models. It can be considered as a collection of object-oriented, network and semistructured models or as some kind of object database. In other words this is a flexible model, you can use any type of database structure depending on task. Such data model has been implemented in DBMS ConteXt. The fundamental unit of information storage of ConteXt is a CLASS. Database Models: Hierarcical, Network, Relational, Object-Oriented, Semistructured, Associative and Context.
UML logo Unified Modeling Language (UML) is a standardized (ISO/IEC 19501:2005), general-purpose modeling language in the field of software engineering. The Unified Modeling Language includes a set of graphic notation techniques to create visual models of object-oriented software-intensive systems. The Unified Modeling Language was developed by Grady Booch, Ivar Jacobson and James Rumbaugh at Rational Software in the 1990s. It was adopted by the Object Management Group (OMG) in 1997, and has been managed by this organization ever since. In 2000 the Unified Modeling Language was accepted by the International Organization for Standardization (ISO) as industry standard for modeling software-intensive systems. The current version of the UML is 2.4.1 published by the OMG in August 2011.
Associative model of data The associative model of data is an alternative data model for database systems. Other data models, such as the relational model and the object data model, are record-based. These models involve encompassing attributes about a thing, such as a car, in a record structure.
Entity-relationship model A sample Entity – Relationship diagram using Chen's notation In software engineering, an entity–relationship model (ER model) is a data model for describing a database in an abstract way.
I found myself reading NoSQL is a Premature Optimization a few minutes ago and threw up in my mouth a little. NoSQL is What? | Jeremy Zawodny's blog
Overview YAGO2s is a huge semantic knowledge base, derived from Wikipedia WordNet and GeoNames. Currently, YAGO2s has knowledge of more than 10 million entities (like persons, organizations, cities, etc.) and contains more than 120 million facts about these entities. YAGO is special in several ways: The accuracy of YAGO has been manually evaluated, proving a confirmed accuracy of 95%. Every relation is annotated with its confidence value.YAGO combines the clean taxonomy of WordNet with the richness of the Wikipedia category system, assigning the entities to more than 350,000 classes.YAGO is an ontology that is anchored in time and space.
Thomas Neumann: D5: Databases and Information Systems (Max-Planck-Institut für Informatik) © 2008 Thomas Neumann Note: A more recent version of the RDF-3X code is available at http://code.google.com/p/rdf3x/. Overview: RDF-3X is the experimental RDF storage and retrieval system described in Thomas Neumann, Gerhard Weikum. RDF-3X: a RISC-style Engine for RDF.