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Titan is a highly scalable graph database optimized for storing and querying massive-scale graphs containing billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users . In addition, Titan provides the following features:
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/C API to read and write data. Oracle NoSQL Driver links with the customer application, providing access to the data via appropriate storage node for the requested key.
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.
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.
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, etcTo use the TinkerPop Graph Database interface you must include these jars in your classpath: orient - commons -*. jar orientdb - core -*. jar blueprints - core -*. jar blueprints - orient - graph -*. jar pipes -*. jar If you're using the TinkerPop Graph Database interface connected to a remote server (not local/embedded mode) include also:
Posted by Peter Neubauer on May 12, 2010 Sections Operations & Infrastructure , Architecture & Design ,
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.
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. Please feel free to DOWNLOAD the evaluation version of DEX Why DEX DEX core technology is based on a combination of different advanced techniques to provide a high performance both in ideal situations, as well as in stress conditions where the database size is larger than the memory available.
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. Example algorithms are nodal-degree, nodal-neighbors, ego-group, graph-density, actor-degree-centrality, group-degree-centrality, actor-closeness-centrality, group-closeness-centrality, actor betweenness-centrality, group-betweenness-centrality, page-rank-centrality, and cliques. Geospatial and temporal primitives combined with SNA functions form an Activity Recognition framework for flexibly analyzing networks and events in large volumes of structured and unstructured data.