new mongodb resource and event streams description

mattmakai · mattmakai · commit 957783c95cc4 · 2020-12-03T10:42:21.000-05:00
diff --git a/content/pages/03-data/12-mongodb.markdown b/content/pages/03-data/12-mongodb.markdown
@@ -67,6 +67,12 @@ command line and query language.
   [Google Cloud Function](/google-cloud-functions.html) 
   to store persistent data while running on a serverless platform.
 
+* [Everything You Know About MongoDB is Wrong!](https://developer.mongodb.com/article/everything-you-know-is-wrong)
+  lists many of the common thoughts developers have about MongoDB and
+  why some of them are misconceptions. This is a good read for
+  developers who used MongoDB several years ago and want to know what
+  major improvements have been made since then.
+
 
 ### MongoDB security
 NoSQL databases can be a weak spot in a production deployment environment,
diff --git a/content/pages/10-working/01-event-streams.markdown b/content/pages/10-working/01-event-streams.markdown
@@ -9,16 +9,24 @@ meta: An event stream is a log of one or more events.
 
 Event streams are a log of one or more "things that happen", which are
 usually referred to as events. Event streams are 
-conceptually focused around things that happen rather than objects, 
-which are the typical storage unit for 
-[relational databases](/databases.html).
+conceptually focused around events than "things" or objects, which are 
+the typical storage unit of [relational databases](/databases.html).
 
 Apache Kafka and Gazette are a popular open source implementations of event 
 streams. Amazon Web Services' Kinesis and 
 [Azure Event-Hubs](https://azure.microsoft.com/en-us/services/event-hubs/)
 are proprietary hosted implementations.
 
 
+## Why do event streams matter to developers?
+The way that data is stored affects how you can work with it. Constraints
+and guarantees like consistency make it easier to code certain applications
+but harder to build other types of applications that need performance in
+different ways. Event streams make it easier to build applications that
+analyze large amounts of constantly-updated data because the events are
+not stored relationally.
+
+
 ## How are event streams typically stored?
 Some applications, such as aggregating millions of sensors, or thousands
 of streaming cameras, constantly output large amounts of data with no breaks. 
