In discussions surrounding the use of PostgreSQL as a graph database, numerous insights emerge regarding its limitations and capabilities. Many users express concerns about the performance of Postgres when handling large datasets typical of timeseries or graph data. The general consensus is that while Postgres can be leveraged for graph representations, it may not perform optimally for extensive graph structures compared to specialized graph databases. There is an ongoing discussion about the integration benefits of using Postgres with general application data versus the need for specialized databases like Neo4j or OrientDB. Users also mention tools like pgRouting and AGE, which enhance Postgres's graph query capabilities, but stress that understanding the limitations of Postgres in this capacity is critical for effective database design. Overall, there is a keen interest in seeing Postgres evolve to better handle complex querying and relational operations associated with graph databases.