programming

02 Oct 2026

DZone Java Zone

Wasm Inside Neo4j: Building the Example That Didn't Exist

In a recent DZone article, Running Sentiment Analysis Inside Neo4j With a Java Plugin, we explored several approaches to running sentiment analysis inside the Neo4j database engine. One of those approaches - embedding a Wasm runtime inside a Java UDF - was described like this:

Theoretically, we could embed a Wasm runtime such as wasmtime inside a Java UDF and execute the VADER Wasm module from within Neo4j, getting Wasm's sandbox guarantees inside Neo4j's plugin model. It's technically feasible but no published working example appears to exist and the complexity cost is high relative to the alternatives. An interesting idea to watch, but not practical today.

02 Oct 2026 6:00pm GMT

Part 3: End-to-End Tracing and Observability Across Goose, agentgateway, and Quarkus

Enterprise context - Acme FinServ. SOC 2 CC7 (system monitoring) requires that Acme can detect and investigate anomalous activity. When an agent-driven workflow touches customer data at 2 AM, "we have logs somewhere" is not an answer an auditor accepts. The distributed trace built in this part is the forensic evidence trail: a single trace ID that ties the Goose prompt to every agentgateway policy decision and every Quarkus tool call, so a post-incident review can reconstruct exactly which agent did what, in what order, and how long each governed hop took.

The Core Problem

In Part 1, we built a Quarkus MCP tool server. In Part 2, we secured it with agentgateway's JWT authentication, RBAC, and ExtMCP guardrails. The architecture works - but when something goes wrong in production, you're flying blind.

02 Oct 2026 1:00pm GMT

01 Oct 2026

DZone Java Zone

Embabel vs LangGraph4j: Two Agentic Philosophies for Investment and Risk Analysis in BFSI

Quick Summary

Both Embabel and LangGraph4j let a Java developer build multi-step AI agents without leaving the JVM.
Embabel hands the framework a goal and a bag of typed actions, and lets a planner decide the order on its own.
LangGraph4j asks the developer to draw the exact graph of nodes and edges by hand.
We will understand both philosophies through a real Embabel agent, a small Kolkata street-crossing example, a comparison table, and finally a bigger question - is Java catching up with Python in enterprise AI work?

Where the Story Starts

If you are a Java developer today, you are watching two worlds collide. On one side are large language models, which grew up almost entirely in Python. On the other side is enterprise Java, which has spent twenty-five years learning to build systems that banks, insurance companies, and hospitals can actually trust.

Two frameworks are now trying to bring these two worlds together on the JVM: Embabel and LangGraph4j. Both help you build an "agent" - a piece of software that uses an LLM to complete a task in several steps, rather than in one single prompt. But the way they think about "steps" is completely different. That difference is what this article is about.

01 Oct 2026 6:00pm GMT