NoSQL Benchmarks NoSQL use cases NoSQL Videos NoSQL Hybrid Solutions NoSQL Presentations Big Data Hadoop MapReduce Pig Hive Flume Oozie Sqoop HDFS ZooKeeper Cascading Cascalog BigTable Cassandra HBase Hypertable Couchbase CouchDB MongoDB OrientDB RavenDB Jackrabbit Terrastore Amazon DynamoDB Redis Riak Project Voldemort Tokyo Cabinet Kyoto Cabinet memcached Amazon SimpleDB Datomic MemcacheDB M/DB GT.M Amazon Dynamo Dynomite Mnesia Yahoo! PNUTS/Sherpa Neo4j InfoGrid Sones GraphDB InfiniteGraph AllegroGraph MarkLogic Clustrix CouchDB Case Studies MongoDB Case Studies NoSQL at Adobe NoSQL at Facebook NoSQL at Twitter



Low Latency at High Concurrency

Russell Sullivan:

Server-side serving “instant” requests means serving more requests (which are usually pretty small) and serving them QUICKLY. Each user will be making loads of smallish requests and need them returned ASAP. The server-side challenge boils down to achieving Low Latency at High Concurrency, which is something of an engineering paradox. Recent advances to tackle what is often referred to as the c10K problem (web servers able to handle ten thousand clients simultaneously) include nginx and node.js.


☞ This recent article about Node.js memory and garbage collection behavior raised some serious questions, many inline with Alex Payne’s (ex-Twitter, BankSimple) ☞ remarks about node.js scalability.

Interesting to note that Russell (aka Jak Sprats) — the guy behind Redis concurrency benchmark — is working on ☞ redisql:

Redisql is a lightweight SQL server AND Redisql is built on top of the NOSQL datastore redis, supports redis data-structures and redis commands and supports (de)normalisation of these data structures (lists,sets,hash-tables) to/from SQL tables. Redisql can also easily import/export tables to/from Mysql for Data-warehousing.

Original title and link: Low Latency at High Concurrency (NoSQL databases © myNoSQL)