riak: All content tagged as riak in NoSQL databases and polyglot persistence
This slidedeck presented by Dirk Deridder and Koen Vanderkimpen at Devoxx 2011 caught my attention not only because it describes pretty clear and succintely what the requirements of a nationwide healthcare system are, but also because I knew another similar case study which was implemented using a different solution.
- highly available
Starting with slide 30, Dirk and Koen detail how Gigaspaces XAP satisfied these system requirements.
Original title and link: Building a Nationwide Healthcase System: Riak and Gigaspaces XAP ( ©myNoSQL)
Congratulations to the Basho guys for closing an additional $5m round of funding. According to Martin Schneider “the funds will be used to make Riak an even better product. We have some seriously awesome plans for additional features, platform capabilities, cloud tools etc.”
Riak already seems like a great product to me—there’s always place for improvements though. I’d say part of the money and a tad more effort should go into making Riak a more popular product.
Details: This is the second round raised this year after the $7.5m announced in June bringing it to a total of $12.5m. The new funding comes from an inside round. Past investors in Basho have included private equity firm Georgetown Partners and Danish systems integrator Trifork AS.
Original title and link: Basho Raises $5mil for Improving Riak ( ©myNoSQL)
Original title and link: The Stories of the Revamped Riak Java Client and Improvements in Python Client ( ©myNoSQL)
Google open sourced a while ago LevelDB , a C++ library that provides an ordered mapping key-value storage. LevelDB performance convinced Basho guys to experiment with adding LevelDB as a storage engine for Riak. And there’s also a benchmark comparing LevelDB with SQLite and Kyoto Cabinet.
The LevelDB project lists the following key features:
- Keys and values are arbitrary byte arrays.
- Data is stored sorted by key.
- Callers can provide a custom comparison function to override the sort order.
- The basic operations are
- Multiple changes can be made in one atomic batch.
- Users can create a transient snapshot to get a consistent view of data.
- Forward and backward iteration is supported over the data.
- Data is automatically compressed using the Snappy compression library.
- External activity (file system operations etc.) is relayed through a virtual interface so users can customize the operating system interactions.
- Detailed documentation about how to use the library is included with the source code.
You can check out also the old thread on Hacker News about LevelDB..
Original title and link: LevelDB: Google’s Fast Persistent Key-Value Store Library ( ©myNoSQL)