Data Partitioning Content on InfoQ
Latest featured content about Data Partitioning

- Topics
- Data Access,
- NoSQL
With the recent NoSQL movement there are several alternative data storage solutions available compared to the traditional relational databases. In this article, author Srinath Perera discusses the various data storage options and what to consider when choosing each of these solutions.

- Topics
- Dynamic Languages,
- Data Access,
- Ruby,
- Deployment / Datacenter,
- Database Design,
- Performance & Scalability,
- Architecture
Ilya Grigorik discusses his company's PostRank algorithm for tracking reader engagement with content. Also: his experience scaling MySQL, Tokyo Cabinet, Ruby HTTP libs, Solr, Amazon EC2 and more.
News about Data Partitioning
- Topics
- Clustering & Caching,
- Java,
- Persistence,
- Data Access,
- Performance & Scalability
VMware releases SQLFire 1.0 a distributed SQL database geared towards high availability and horizontal scalability which offers table replication, table partitioning and parallel execution of queries.
- Topics
- Persistence,
- Data Access,
- Java
JBoss Releases Hibernate 4.0 which comes with Multi-tenancy support, the introduction of a standard mechanism for writing Hibernate extensions, initial refactorings towards OSGI and several other cleanups.
- Topics
- Operations,
- Data Access,
- Deployment / Datacenter,
- Database Design,
- Performance & Scalability,
- Data Warehousing,
- Architecture
The Hadoop Summit of 2010 included presentations from a number of large scale users of Hadoop and related technologies. Notably, Facebook presented a keynote and details information about their use of Hive for analytics. Mike Schroepfer, Facebook's VP of Engineering delivered a keynote describing the scale of their data processing with Hadoop.
- Topics
- Data Access,
- Performance & Scalability,
- Ruby
In this databases roundup we take a look at DataFabric, FiveRun's recently open sourced data sharding plug-in for ActiveRecord. Also: a look at speeding up Postgres data access using the asynchronous client API and Ruby 1.9's Fibers.