Riak: All content tagged as Riak in NoSQL databases and polyglot persistence
If you are asked to compare (or you just wonder about) the performance of link walking and map-reduce in Riak keep in mind the following details of how the two mechanism are implemented:
My emphasis on Bryan Fink’s email from Riak’s mailing list.
Original title and link: Riak Performance of Link Walking vs MapReduce ( ©myNoSQL)
Auric Systems International, a leader in merchant transaction processing solutions, relies on Basho’s Riak to power its PaymentVault(TM) solution for PCI compliance. Riak was chosen because of the simplicity by which it replicates data, including stored encrypted credit card tokenized data, its ability to automate the aging of data, and its availability as open source.
After spending half an hour on the pcisecuritystandards site I still couldn’t figure out what the Level 1 PCI compliancy means to understand what Riak brought to the table.
If you thought all systems in the financial sector need transactions and are using relational databases, then I guess you were wrong. Read also the Card payment sytems and the CAP theorem to see the requirements of another financial service.
Original title and link: Riak Used by Auric Systems to Meet PCI Compliance Requirements ( ©myNoSQL)
Old Quora question with very good answers.
- (pro) can (potentially) query live data
- (pro) can (conceptually) be highly efficient at joining data sets that are identically sharded on the join key (the joins can be pushed down into the key-value store itself)
- (con) full scans (the most common pattern for map-reduce) is most likely to be much faster with raw file system access
- (con) because of the better decoupling of computation and storage in the GFS+Map-Reduce model - tolerating hot spots (resulting from MR jobs) is much easier
- (con) key-value stores are rarely arranged to have schemas optimized for analytics
Original title and link: Pros and Cons of Using MapReduce With Distributed Key-Value Stores: HBase, Cassandra, Riak ( ©myNoSQL)
Eventual and Strong Consistency, Sloppy and Strict Quorums, and Other Lessons and Thoughts on Distributed Systems
Anything I’d write would just steal from your time to read and think about the email Joseph Blomstedt posted to the Riak list.
Original title and link: Eventual and Strong Consistency, Sloppy and Strict Quorums, and Other Lessons and Thoughts on Distributed Systems ( ©myNoSQL)
If you take a look at the topic of security in the NoSQL context, you’ll notice that things are far from being perfect. So, any contributions in this area are welcome. Patrik Karlsoon added a couple of network exploration Nmap scripts for Riak, Redis, and Memcached. And while these will not help much with security they might proove useful for managing your NoSQL deployments:
Added the script riak-http-info that lists version and statistics information from the Basho Riak distributed database.
Added the script memcached-info that lists version and statistics information from the distributed memory object caching service memcached
Added the script redis-info that lists version and statistic information gathered from the Redis network key-value store.
Added the redis library and the script redis-brute that performs brute force password guessing against the Redis network key-value store.
Original title and link: Nmap Scripts for Riak, Redis, Memcached ( ©myNoSQL)
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)