Merge pull request #33 from kuzudb/patch-fixes

Patch fix for image sizing

src/content/post/2022-11-15-meet-kuzu.md

@@ -10,8 +10,6 @@ authors: ["team"]
 tags: ["vision"]
 ---
 
-# Meet Kùzu 🤗
-
 Today we are very excited to make an initial version of [Kùzu public on github](https://github.com/kuzudb/kuzu)! 
 Kùzu[^1] is a new embeddable property graph database management system (GDBMS) that is 
 designed for high scalability and very fast querying. We are releasing 

src/content/post/2023-01-12-what-every-gdbms-should-do.md

@@ -209,7 +209,7 @@ A classic example we like using is a Twitter friend recommendation engine that i
 the following rule: If a user A follows two users B and C, who both follow D, recommend
 D to A. This is the pattern:
 
-![](/img/2023-01-12-what-every-gdbms-should-do/diamond-pattern.png)
+<Image src="/public/img/2023-01-12-what-every-gdbms-should-do/diamond-pattern.png" width="500" />
 
 The whitepapers of existing GDBMSs are full of these patterns, e.g., branching trees, money laundering circles,
 cliques of customers who buy similar items, etc. These correspond to complex
@@ -324,7 +324,7 @@ a particular application domain we are currently excited
 about and we want to see Kùzu used in: graph data science in the python ecosystem!
 This figure from my CIDR slides describes this vision pictorially:
 
-![Kùzu as a GDBMS for Graph Data Science Pipelines](/img/2023-01-12-what-every-gdbms-should-do/kuzu-as-gdbms-of-gds.png)
+<Image src="/img/2023-01-12-what-every-gdbms-should-do/kuzu-as-gdbms-of-gds.png" width="600" /> 
 
 Suppose you are building a graph analytics, machine learning, or visualization
 pipeline from raw record files on disk. You will want to model your raw records 

src/content/post/2023-01-20-factorization.md

@@ -283,7 +283,7 @@ When designing the query processor of Kùzu, we had 3 design goals:
 Kùzu has a vectorized query processor, which is the common wisdom
 in analytical read-optimized systems. 
 
-![](/img/2023-01-20-factorization/factorized-vectors.png)
+<Image src="/img/2023-01-20-factorization/factorized-vectors.png" width="600" /> 
 
 Vectorization, in the context of DBMS query processors 
 refers to the design where operators pass a set of tuples, 1024 or 2048, 

src/content/post/2023-02-22-wcoj.md

@@ -245,7 +245,7 @@ In this case, we will produce the triangle (`a`=1, `b`=0, `c`=1001)
 The result of this computation will produce the third and final 
 output table in the figure.
 
-![](/img/2023-02-22-wcoj/wcoj-4-clique.png)
+<Image src="/img/2023-02-22-wcoj/wcoj-4-clique.png" width="400" />
 
 Note that this process did not produce the 2-paths as an intermediate step, 
 which is how wcoj algorithms fix for the sub-optimality of binary join algorithms.

src/content/post/2023-07-19-iamgraphviz.md

@@ -10,8 +10,6 @@ authors: ["chang", {"name": "Chris Norman", "image": "https://www.commonfate.io/
 tags: ["visualization"]
 ---
 
-## IAMGraphViz Overview
-
 [Common Fate](https://www.commonfate.io/)  is a framework for managing complex cloud permissions. They provide tools to simplify access at scale to AWS, Azure, and Google Cloud accounts. You can learn about what you can do with Common Fate on [their website](https://www.commonfate.io/). Here, we will talk about a recent proof of concept graph visualization tool called IAMGraphViz that [Chang Liu](https://www.linkedin.com/in/mewim/) (who is coauthoring this post) and I developed using Kùzu! IAMGraphViz is intended for infrastructure engineers to dig deep into the permission assignments in AWS IAM Identity Center using graph visualization. Using IAMGraphViz, one can easily visualize who has what type of access to different accounts on AWS as well as how they have access to these accounts. This is all done by analyzing the paths from users to accounts in a graph visualization, where the nodes and edges model users, accounts, groups, group memberships, permission sets and other entities in the AWS IAM Identity Center system.
 
 The IAMGraphViz project is designed and implemented as a web application using a graph DBMS (GDBMS) to store and retrieve data. Before landing on Kùzu, we surveyed using several other GDBMSs, such as Neo4j, but they were all harder to use. Neo4j, for example, requires hosting a separate database. We then discovered Kùzu, which only required a `pip install` and import statement and we could simply embed it into our application. In this project our datasets could fit entirely onto a single compute node,and so Kùzu was far simpler for us to work with than alternatives. Kùzu is also far cheaper and more serverless-friendly than running a separate database.
@@ -20,7 +18,7 @@ This post follows the [Colab](https://colab.research.google.com/drive/1fotlNnOj1
 
 So let's get to it!
 
-## Quick AWS IAM Overview
+## Overview of AWS IAM
 
 We will use the data model shown in the figure below that faithfully (but partially) models the
 core concepts of AWS IAM permission management. Let's first review these concepts, all

src/content/post/2023-08-28-kuzu-v-0.0.8.md

@@ -9,8 +9,6 @@ authors: ["team"]
 tags: ["cypher", "data-type", "performance"]
 ---
 
-# Kùzu 0.0.8 Release
-
 We're here to introduce Kùzu 0.0.8, which is a minor bug-fix release together with some performance optimizations:
 
 - Fixed a major bug in COPY on large datasets. [PR 1963](https://github.com/kuzudb/kuzu/pull/1963)

src/content/post/2023-10-19-kuzu-v-0.0.11.md

@@ -9,6 +9,6 @@ authors: ["team"]
 tags: ["concurrency"]
 ---
 
-We release Kùzu 0.0.11, another minor release. The main new feature of this release is read-only access mode for the database on Linux. The read-only mode enables the upcoming [Kùzu UI](https://github.com/kuzudb/kuzu-ui) to optionally open a database in read-only mode while allowing other applications to access the same database concurrently.
+Another minor release, Kùzu 0.0.11, is here! The main new feature of this release is read-only access mode for the database on Linux. The read-only mode enables the upcoming [Kùzu UI](https://github.com/kuzudb/kuzu-ui) to optionally open a database in read-only mode while allowing other applications to access the same database concurrently.
 
 For more detailed information about the changes in this release, please see [here](https://github.com/kuzudb/kuzu/releases/tag/v0.0.11).

src/content/post/2023-10-25-kuzuexplorer.md

@@ -10,7 +10,7 @@ authors: ["chang"]
 tags: ["visualization"]
 ---
 
-Today, we are happy to release KùzuExplorer, which is Kùzu's browser-based frontend to
+Today, we are happy to announce the release of KùzuExplorer, a browser-based frontend for Kùzu to
 visualize and explore database schemas and query results in the form of a graph, table, or in JSON.
 This is a very useful tool for exploring databases and debugging applications during prototyping
 phase. This post describes a brief overview of the main features of KùzuExplorer with pointers to

src/layouts/Posts.astro

@@ -33,7 +33,7 @@ type PostType = {
           {post.data.heroImage && (
             <a href={`/post/${post.slug}/`}>
             <center>
-                <figure class="max-w-96 h-36 block bg-white border-2 border-zinc-200">
+                <figure class="max-w-96 h-40 block bg-white border-2 border-zinc-200">
                 <Image
                     src={post.data.heroImage}
                     alt={post.data.title}

src/styles/global.css

@@ -48,7 +48,7 @@
   }
 
   article img {
-    @apply rounded w-full;
+    @apply rounded;
   }
 
   th {