diff --git a/README.md b/README.md index 67f57fc..b2b41a2 100644 --- a/README.md +++ b/README.md @@ -241,7 +241,7 @@ An updated and curated list of selected readings to illustrate High Scalability, * [MPH: Fast and Compact Immutable Key-Value Stores at Indeed](http://engineering.indeedblog.com/blog/2018/02/indeed-mph/) * [zBase: High Performance, Elastic, Distributed Key-Value Store at Zynga](https://www.zynga.com/blogs/engineering/zbase-high-performance-elastic-distributed-key-value-store-2) * [Venice: Distributed Key-Value Database at Linkedin](https://engineering.linkedin.com/blog/2017/02/building-venice-with-apache-helix) - * [Column Databases (Cassandra, HBase)](https://aws.amazon.com/nosql/columnar/) + * [Column Databases (Cassandra, HBase, Redshift)](https://aws.amazon.com/nosql/columnar/) * [Consistent Hashing in Cassandra](https://blog.imaginea.com/consistent-hashing-in-cassandra/) * [Understanding Gossip (Cassandra Internals)](https://www.youtube.com/watch?v=FuP1Fvrv6ZQ) * [When NOT to use Cassandra?](https://stackoverflow.com/questions/2634955/when-not-to-use-cassandra) @@ -256,6 +256,7 @@ An updated and curated list of selected readings to illustrate High Scalability, * [Imgur Notification: From MySQL to HBASE at Imgur](https://blog.imgur.com/2015/09/15/tech-tuesday-imgur-notifications-from-mysql-to-hbase/) * [Improving HBase Backup Efficiency at Pinterest](https://medium.com/@Pinterest_Engineering/improving-hbase-backup-efficiency-at-pinterest-86159da4b954) * [ClickHouse - Open Source Distributed Column Database at Yandex](https://clickhouse.yandex/) + * [Scaling Redshift without Scaling Costs at GIPHY](https://engineering.giphy.com/scaling-redshift-without-scaling-costs/) * [Document Databases (MongoDB, SimpleDB, CouchDB)](https://msdn.microsoft.com/en-us/magazine/hh547103.aspx) * [eBay: Building Mission-Critical Multi-Data Center Applications with MongoDB](https://www.mongodb.com/blog/post/ebay-building-mission-critical-multi-data-center-applications-with-mongodb) * [MongoDB at Baidu: Multi-Tenant Cluster Storing 200+ Billion Documents across 160 Shards](https://www.mongodb.com/blog/post/mongodb-at-baidu-powering-100-apps-across-600-nodes-at-pb-scale)