Product
LevelDB is an exciting new entrant into the pantheon of embedded databases, notable both for its pedigree, being authored by the makers of the now mythical Google MapReduce and BigTable products, and for its emphasis on efficient disk based random access using log-structured-merge (LSM) trees. The plan is to keep
Product
What do you get when you take a SQL database and start a new implementation from scratch, taking advantage of the latest research and modern hardware? Mike Stonebraker, the sword wielding Johnny Appleseed of the database world, hopes you get something like his new database, VoltDB: a pure SQL, pure
Product
I met the CodeFutures folks, makers of dbShards, at Gluecon. They occupy an interesting niche in the database space, somewhere between NoSQL, which jettisons everything SQL, and high end analytics platforms that completely rewrite the backend while keeping a SQL facade. High concept: I think of dbShards as a sort
Paper
Cloud computing promises a number of advantages for the deployment of data-intensive applications. Most prominently, these include reducing cost with a pay-as-you-go pricing model and (virtually) unlimited throughput by adding servers if the workload increases. At the Systems Group, ETH Zurich, we did an extensive end-to-end performance study to compare
databases
Terrastore is a new-born document store which provides advanced scalability and elasticity features without sacrificing consistency. Here are a few highlights: * Ubiquitous: based on the universally supported HTTP protocol. * Distributed: nodes can run and live everywhere on your network. * Elastic: you can add and remove nodes dynamically to/from your
databases
This article not about Mariah Carey, or its song. It's about Storing System, Database. First let's describe what means by odds: In my social network, I found 93% of the mainstream developers sanctify the database, or at least consider it in any data persistence challenge as
BigTable
In this podcast, we interview Jonathan Ellis about how Facebook's open sourced Cassandra Project took lessons learned from Amazon's Dynamo and Google's BigTable to tackle the difficult problem of building a highly scalable, always available, distributed data store.
Paper
Relational databases, document databases, and distributed hash tables get most of the hype these days, but there's another option: graph databases. Back to the future it seems. Here's a really interesting paper by Marko A. Rodriguez introducing the graph model and it's extension to
Hadoop
Geir Magnusson from 10gen presented a talk titled Cloud Data Persistence or ‘We’re in a database reneaissance - pay attention” today at QCon London 2009. The main message of his talk was that “physical limitations of today’s technology combined with the computational complexity of conventional relational databases are
Oracle
One of the most interesting new features of Oracle 11 is the new function result caching mechanism. Until now, making sure that a PL/SQL function gets executed only as many times as necessary was a black art. The new caching system makes that quite easy -- here is how