Add sageDB and Modify README

README.md

@@ -12,7 +12,7 @@ If you are reading this and taking the effort to understand these papers, we wou
   4. [Columnar Databases](#column)
   5. [Data-Parallel Computation](#data-parallel)
   6. [Consensus and Consistency](#consensus)
-  7. [Trends (Cloud Computing, Warehouse-scale Computing, New Hardware)](#trends)
+  7. [Trends (Cloud Computing, Warehouse-scale Computing, New Hardware, Machine Learning)](#trends)
   8. [Miscellaneous](#misc)
   9. [External Reading Lists](#external)
 
@@ -83,12 +83,14 @@ Columnar storage and column-oriented query engine are critical to analytical wor
 * [CAP Twelve Years Later: How the "Rules" Have Changed](papers/cap.pdf) (2012): The CAP theorem, proposed by Eric Brewer, asserts that any net­worked shared-data system can have only two of three desirable properties: Consistency, Availability, and Partition-Tolerance. A number of NoSQL stores reference CAP to justify their decision to sacrifice consistency. This is Eric Brewer's writeup on CAP in retrospective, explaining "'2 of 3' formulation was always misleading because it tended to oversimplify the tensions among properties."
 
 
-## <a name='trends'> Trends (Cloud Computing, Warehouse-scale Computing, New Hardware)
+## <a name='trends'> Trends (Cloud Computing, Warehouse-scale Computing, New Hardware, Machine Learning)
 
 * [A View of Cloud Computing](papers/cloud-computing.pdf) (2010): This is THE paper on Cloud Computing. This paper discusses the economics and obstacles of cloud computing (referring to the elasticity of resources, not the consumer-facing "cloud") from a technical perspective. The obstacles presented in this paper will impact design decisions for systems running in the cloud.
 
 * [The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines](papers/data-center-computer.pdf): Google's Luiz André Barroso and Urs Hölzle explains the basics of data center hardware and software for warehouse-scale computing. There is an [accompanying video](http://dl.acm.org/citation.cfm?id=2019527&bnc=1). The video talks about the importance of cutting long-tail latency in massively parallel systems. The other key idea is the disaggregation of resources. Technologies such as GFS/HDFS already disaggregate disks because of high network bandwidth, but yet to see the same trend applying to DRAMs because that'd require low-latency networking.
 
+* [SageDB: A Learned Database System](papers/sageDB.pdf) (2019): SageDB is an emerging database system jointly proposed by Google and MIT and Brown University researchers. It presents a radical new approach to build database systems, by using using machine learning models combined with program synthesis to generate system components.
+
 
 ## <a name='misc'> Miscellaneous