HBase: Bigtable-like structured storage for Hadoop HDFS
Just as Google's Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Hadoop Core. Data is organized into tables, rows and columns. An Iterator-like interface is available for scanning through a row range (and of course there is the ability to retrieve a column value for a specific key). Any particular column may have multiple versions for the same row key.
Performance and scalability.
In a web-driven world, datasets are larger than ever before – with “web scale” becoming the term of choice to describe the ultimate size of problems.
It is used at LinkedIn for certain high-scalability storage problems where simple functional partitioning is not sufficient. It is still a new system which has rough edges, bad error messages, and probably plenty of uncaught bugs. Let us know if you find one of these, so we can fix it.
Welcome to MongoDB
MongoDB is a high-performance, open source, schema-free document-orienteddata store that's easy to deploy, manage and use. It's network accessible, written in C++ and offers the following features :
- Collection oriented storage - easy storage of object-style data
- Full index support, including on inner objects
- Query profiling
- Replication and fail-over support
- Efficient storage of binary data including large objects (e.g. videos)
- Auto-sharding for cloud-level scalability (Q209)
High performance, scalability, and reasonable depth of functionality are the goals for the project. Deep transaction support is not a goal of the system.