Posts Tagged ‘databases’

NoSQL’s Data Modeling Advantages


Jennifer Zaino recently wrote an article for our sister website DATAVERSITY on the evolving field of NoSQL databases. Zaino wrote, “Hadoop Hbase. MongoDB. Cassandra. Couchbase. Neo4J. Riak. Those are just a few of the sprawling community of NoSQL databases, a category that originally sprang up in response to the internal needs of companies such as Google, Amazon, Facebook, LinkedIn, Yahoo and more – needs for better scalability, lower latency, greater flexibility, and a better price/performance ratio in an age of Big Data and Cloud computing. They come in many forms, from key-value stores to wide-column stores to data grids and document, graph, and object databases. And as a group – however still informally defined – NoSQL (considered by most to mean ‘not only SQL’) is growing fast. The worldwide NoSQL market is expected to reach $3.4 billion by 2018, growing at a CAGR of 21 percent between last year and 2018, according to Market Research Media. Read more

NoSQL and The Next Generation of Databases


Mark van Rijmenam of Smart Data Collective recently wrote, “The past decades organisations have been working with relational databases to store their structured data. In the big data era however, these types of databases are not sufficient anymore. Although they made a huge difference in the database world and unlocked data for many applications, relational databases miss some important characteristics for the big data era. NoSQL databases are the answer that solves many of these problems. It is a completely new way of thinking about databases… Read more

Bringing Together the Cloud & Semantic Tech

Eric Little of Bio-ITWorld recently discussed how private cloud technologies can be used to improve semantic technologies. He writes, “While semantic technologies provide a sophisticated way of modeling complex relationships between data, the graphs that are created within semantic solutions can quickly grow to enormous sizes, given that they capture not only the elements contained within an enterprise’s raw data, but the added litany of related facts and relationships generated by automated reasoning, where 10-100 times as much new data can be generated from a single data source. As an example, imagine taking one’s raw assay data on a given compound, then linking it to all known data about related clinical studies and phenotypic effects, as well as underlying genomics data.” Read more

Sharing Data in the Biotech Community

Vivien Marx of reports, “In January, over 50 researchers from 30 academic and commercial organizations agreed on a standard for describing data sets. The BioSharing initiative, comprising both researchers and publishers, launched the Investigation-Study-Assay (ISA) Commons, which promises to streamline data sharing among different databases. Life scientists have thousands of databases, over 300 terminologies and more than 120 exchange formats at their disposal, says BioSharing co-founder Susanna-Assunta Sansone of the University of Oxford. In this era of collaborative big science, researchers only move forward by ‘walking together.’ Although increased data sharing is central to scientific progress and is attracting attention from many quarters, standards are only some of the stars that must align to make it possible.” Read more

Dydra Envisions RDF As A Cloud Service

The cloud cometh to the Semantic Web in many ways, and one of the newest is in the form of Dydra, an RDF cloud service that’s aiming to take the pain out of dealing with your semantic data. The product of Datagraph Inc., one of the New Orleans-based startups with seed funding from Chris Schultz’ Voodoo Ventures, Dydra is essentially a database-as-a-service for storing, publishing, and querying RDF data on its multitenant architecture. The idea is to let users focus on data consumption, and let the service focus on things like scalability and data store system administration.

“We’re removing two things – the computer and the stuff you need to run the computer and software itself,” says Datagraph co-founder Ben Lavender. Currently available only to beta testers, the plan is to let users avoid having to get licenses or become involved in long-winded setup procedures: “Just click a button to create the database and it appears,” is how Lavender puts it. “There’s nothing between you and actually using it.”

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