Graph
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The Oracle NoSQL Database is a distributed key-value database. It is designed to provide highly reliable, scalable and available data storage across a configurable set of systems that function as storage nodes. Data is stored as key-value pairs, which are written to particular storage node(s), based on the hashed value of the primary key. Storage nodes are replicated to ensure high availability, rapid failover in the event of a node failure and optimal load balancing of queries. Customer applications are written using an easy-to-use Java API to read and write data. The NoSQL Database links with the customer application, providing access to the data via the appropriate storage node for the requested key-value.
NoSQL Database Technical Overview
Lately I've been reading more cases were different people have started to realize the limitations of the NoSQL promise to database scalability. Note the references below: Take MongoDB for example.
High Scalability - High Scalability - NoSQL Pain? Learn How to Read/write Scale Without a Complete Re-write
NoSQL, NewSQL and Beyond
The 451 Group has published last week the conclusions of a report detailing the growing set of options in the information management space. In the process they also clarified what they meant by "NewSQL" . “NewSQL” is our shorthand for the various new scalable/high performance SQL database vendors. [...NewSQL vendors] have in common the development of new relational database products and services designed to bring the benefits of the relational model to distributed architectures, or to improve the performance of relational databases to the extent that horizontal scalability is no longer a necessity. We would include (in no particular order) Clustrix, GenieDB, ScalArc, Schooner, VoltDB, RethinkDB, ScaleDB, Akiban, CodeFutures, ScaleBase, Translattice, and NimbusDB, as well as Drizzle, MySQL Cluster with NDB, and MySQL with HandlerSocket. The latter group includes Tokutek and JustOne DB.Visual Guide to NoSQL Systems - Nathan Hurst's Blog
There are so many NoSQL systems these days that it's hard to get a quick overview of the major trade-offs involved when evaluating relational and non-relational systems in non-single-server environments. I've developed this visual primer with quite a lot of help (see credits at the end), and it's still a work in progress, so let me know if you see anything misplaced or missing, and I'll fix it. Without further ado, here's what you came here for (and further explanation after the visual). Note: RDBMSs (MySQL, Postgres, etc) are only featured here for comparison purposes. Also, some of these systems can vary their features by configuration (I use the default configuration here, but will try to delve into others later).
GraphDatabaseTinkerpop - orient - Graph Database and Tinkerpop - NoSQL document database light, portable and fast. Supports ACID Tx, Indexes, asynch queries, SQL layer, clustering, etc - Google Project Hosting
Even if OrientDB already provides own APIs to handle graphs in easy way, starting from release 0.9.22 OrientDB provides an implementation of the Tinkerpop Blueprints APIs. Tinkerpop is a complete stack of projects to handle Graphs: Blueprints provides a collection of interfaces and implementations to common, complex data structures.
Graph Databases, NOSQL and Neo4j
Introduction Of the many different datamodels , the relational model has been dominating since the 80s, with implementations like Oracle , MySQL and MSSQL - also known as Relational Database Management System (RDBMS). Lately, however, in an increasing number of cases the use of relational databases leads to problems both because of Deficits and problems in the modeling of data and constraints of horizontal scalability over several servers and big amounts of data. There are two trends that bringing these problems to the attention of the international software community:
I received some constructive criticism regarding my previous blog in NoSQL patterns that I covered only the key/value store but have left out Graph DB. The Property Graph Model A property graph is a collection of Nodes and Directed Arcs. Each node represents an entity and has an unique id as well as a Node Type.
NoSQL GraphDB
InfiniteGraph™ Enables Development of Next-Gen Applications that Connect the Dots on a Global Scale. Sunnyvale, CA – August 16, 2011 – InfiniteGraph, the number one commercial, distributed and scalable graph database, is changing the world by enabling a new, cost effective, and efficient way of navigating multiple types of databases for discovery of deeper and more relevant intelligence, enabling real-time decision support. By being able to understand deeper, more complex relationships within existing and new data, companies can leverage social network analysis and business intelligence to achieve greater efficiencies and competitive advantage. InfiniteGraph can support any number of applications and systems around the analysis of relationships in big data, and does all of this across any number and size of data volumes, in real-time.
NoSQL Databases - NoSQL Databases
db4o : API: Java, C#, .Net Langs , Protocol: language , Query Method: QBE (by Example), Soda, Native Queries, LINQ (.NET) , Replication: db4o2db4o & dRS to relationals , Written in: Java , Cuncurrency: ACID serialized , Misc: embedded lib, Links : DZone Refcard #53 » , Book » , Versant : Languages/Protocol: Java, C#, C++, Python . Schema: language class model (easy changable).
NOSQL Databases
overview VertexDB is a high performance graph database server that supports automatic garbage collection. It uses the HTTP protocol for requests and JSON for it's response data format and the API is inspired by the FUSE filesystem API plus a few extra methods for queries and queues. It's implementation is currently built on top of TokyoCabinet and libevent.
steve dekorte - projects - open source - vertexdb
TinkerPop
Blueprints is a property graph model interface with provided implementations. Databases that implement the Blueprints interfaces automatically support Blueprints-enabled applications. Pipes is a dataflow framework that enables the splitting, merging, filtering, and transformation of data from input to output.DEX is a high-performance and scalable graph database management system written in Java and C++. One of its main characteristics is its query performance for the retrieval and exploration of large networks. Its implementation with very light specialized structures allows analysing and querying billions of objects at very low storage cost. New solutions for new needs. The emergence of huge networks such as the Internet, geographical systems, transportation or social network databases, has brought the need to manage information with inherent graph-like nature. In these scenarios, users are not only keen on retrieving plain tabular data from entities, but also relationships with other entities using explicit or implicit values and links to obtain more elaborated information.
performance in action
Spring Data Neo4j E-book Available Now!
neo4j open source nosql graph database »
Geospatial and Temporal Reasoning AllegroGraph stores geospatial and temporal data types as native data structures. Combined with its indexing and range query mechanisms, AllegroGraph lets you perform geospatial and temporal reasoning efficiently. Social Networking Analysis AllegroGraph includes an SNA library that treats a triple-store as a graph of relations, with functions for measuring importance and centrality as well as several families of search functions.