Java profiling tools vary in how deeply they analyze JVM and application performance. Free tools like VisualVM and async-profiler offer accessible JVM monitoring and low-overhead profiling, while commercial options like YourKit and JProfiler provide more detailed CPU, memory, thread, and application-level analysis. Azul’s profiling stack combines production profiling through Mission Control with dedicated GC log analysis through GC Log Analyzer.
Here’s how three of the top 9 tools compare:
| Tool | Best for | Starting price |
|---|---|---|
| Azul (Mission Control + GC Log Analyzer) | Production profiling on performance-critical JVMs | Included with Core/Prime subscriptions |
| YourKit Java Profiler | Deep CPU and memory profiling in development | $449/yr (single seat) |
| async-profiler | Low-overhead sampling in production | Free (open source) |
A $1m Cloud Bill Makes Every Performance Problem Expensive
Large cloud environments can get expensive quickly. According to Flexera’s 2026 State of the Cloud Report, 76% of large enterprises now spend more than $5 million per month on public cloud services.
When you are running Java workloads at that scale, even small performance inefficiencies can translate into significant infrastructure costs. A long GC pause, excessive object allocation, or an inefficient code path could increase latency, waste compute resources, and, in latency-sensitive applications, contribute to missed trades or failed SLAs.
Java profiling tools help you find what’s happening inside the JVM so you can identify these bottlenecks and troubleshoot their root causes.
But profiling in development and profiling in production aren’t the same job. A tool that adds noticeable overhead in a development environment might be unsuitable for a latency-sensitive trading system. And a heap dump analyzer that handles a 2 GB heap comfortably may struggle with 64 GB.
We reviewed 9 Java profiling tools based on how well they perform in both development and production profiling. Here’s what each offers.
Why Listen to Us?
At Azul, we built Mission Control and GC Log Analyzer to help teams monitor, profile, and troubleshoot Java performance.
Organizations that use our products have reported significant performance and efficiency gains. For example, Workday reduced total Java pause time from 40,000 seconds per JVM per week to 14 seconds, improved operational efficiency by over 95%, and eliminated more than 42,000 person-hours of performance tuning and troubleshooting.
What Are Java Profiling Tools?
Java profiling tools measure what’s happening inside your JVM at runtime. They capture CPU usage per method, memory allocation patterns, GC behavior, thread states, and lock contention. Together, these metrics map where your app spends its time and memory.
How We Evaluated the Tools on This List
We assessed each tool based on five factors:
Production-readiness – can you run it live without degrading performance?
Profiling depth – does it cover CPU, memory, GC, and threads, or just one?
Pricing model – per-seat, per-host, usage-based, or free?
Integration – does it work with your JVM, IDE, and observability stack?
GC analysis – how well does it help you understand garbage collection behavior and its impact on application performance?
The 9 Best Java Profiling Tools: Detailed Reviews
| Tool | Best for | Starting price |
|---|---|---|
| Azul (Mission Control + GC Log Analyzer) | Production profiling on performance-critical JVMs | Included with Core/Prime subscriptions |
| YourKit Java Profiler | Deep CPU and memory profiling in development | $449/yr (single seat) |
| JProfiler | Visual profiling with database and JEE analysis | $768 (with support) |
| async-profiler | Low-overhead CPU and allocation sampling in production | Free (open source) |
| Eclipse MAT | Heap dump analysis and memory leak investigation | Free (open source) |
| IntelliJ Profiler | Profiling without leaving the IDE | free inside IntelliJ IDEA Ultimate |
| Datadog Continuous Profiler | Always-on profiling across distributed services | $19/host/month (standalone) |
| New Relic APM | Full-stack observability with Java profiling | Usage-based (free tier available) |
| VisualVM | Free, general-purpose JVM monitoring | Free (open source) |
1. Azul (Mission Control + GC Log Analyzer)
At Azul, we have a stack of products built for Java performance profiling and optimization.
First is Azul Mission Control, a monitoring, profiling, and troubleshooting tool for Java applications running on Java 8, Java 11, or later JVMs that support Flight Recorder. It’s built on the open-source JDK Mission Control project and works with JDK Flight Recorder to capture runtime data with very little overhead. We ship it free with every Azul Core and Azul Prime subscription.
Next, our GC Log Analyzer goes deeper into garbage collection. It parses GC logs from OpenJDK distributions and provides graphs covering heap usage, pause times, and JIT compilation. For Azul Prime workloads, it can also analyze C4 garbage collection data captured in GC logs.
What makes our profiling stack different is that we designed it with the JVM in mind, not as an afterthought. Mission Control connects directly to live JVMs, giving you visibility into CPU, memory, threads, and GC behavior. Because it uses JFR under the hood, it provides low-overhead profiling and monitoring you can use in production, including on latency-sensitive systems.
And when profiling reveals that the JVM itself is contributing to your performance problems, you can address them at the runtime level with Azul Prime.
Its C4 garbage collector eliminates stop-the-world pauses, and customer LMAX reported 48% faster performance than running on OpenJDK alone, a result that combined Azul Prime with Azul-assisted application tuning. When Hua Nan Securities moved to Prime, they improved trading system efficiency by 35% while cutting infrastructure costs by 30%.
Key features
JFR-based live profiling: Connect to running JVMs and capture CPU, memory, thread, and I/O events with low overhead suitable for production use
GC Log Analyzer: Parse and visualize GC logs from any OpenJDK distribution, covering heap, pause time, and JIT activity
C4 pauseless GC diagnostics (Prime): Analyze C4 garbage collection behavior from GC logs
ReadyNow warmup analysis: View ReadyNow statistics in GC Log Analyzer to understand JVM warmup behavior and restart performance
Multi-JVM connection: Monitor multiple JVMs from a single Mission Control console
Cross-platform support: Run on Windows, Linux, and macOS, and connect to any JVM on Java 8 or later
Jolokia integration: Connect to JVMs through Jolokia when direct JMX access isn’t available
Pricing
Mission Control community builds are free to download. Mission Control and GC Log Analyzer are both included with every Azul Core and Azul Prime subscription. Prime is priced per vCore annually, with volume discounts. Contact our sales team for a custom quote.
Pros
Built by Azul’s Java engineering team, the largest outside Oracle, so profiling data reflects exactly how the runtime behaves
GC Log Analyzer provides dedicated garbage-collection analysis beyond what general-purpose profilers typically offer
Production-safe overhead using JFR, even on latency-sensitive financial systems
Cons
GC Log Analyzer’s full SA build requires an Azul subscription, so teams not on Core or Prime can’t access it
Prime pricing requires contacting Azul, so you can’t calculate total costs through a self-serve pricing page
2. YourKit Java Profiler
YourKit is a commercial Java profiler that combines CPU and memory profiling with thread analysis in a standalone desktop app. It supports CPU sampling and tracing modes and integrates with IntelliJ IDEA, Eclipse, and NetBeans. You can connect it to local and remote JVMs.
Its biggest strength is memory profiling. It lets you inspect individual objects, see where they were allocated, analyze what they retain, and compare CPU and memory snapshots. If you’re hunting memory leaks, that level of detail can save hours.
Key features
CPU profiling (sampling and tracing): Switch between low-overhead sampling and exact call-count tracing depending on how deep you need to go
Memory allocation recording: Track every object allocation and pinpoint the methods generating the most garbage
Thread profiling and deadlock detection: Visualize thread states over time and detect deadlocks automatically
Integration with major IDEs: Profile directly from IntelliJ IDEA, Eclipse, or NetBeans without switching tools
Pricing
Single-seat annual subscription: $449 for Basic support or $579 for Advanced support
Single-seat perpetual license: $549 for Basic support or $713 for Advanced support
Five-seat annual subscription: $1,259 for Basic support or $1,639 for Advanced support
Five-seat perpetual license: $1,539 for Basic support or $1,999 for Advanced support
Single-user floating annual subscription: $2,249 for Basic support or $2,919 for Advanced support
Single-user floating perpetual license: $2,749 for Basic support or $3,569 for Advanced support
Enterprise: Custom pricing for companies with more than 50 profiler installations
Academic: $99/year for a single-seat license or $999/year for an institution-wide license
Open source: Free for qualifying non-commercial open-source projects
Pros
Detailed memory profiling helps you trace object retention and allocation back to the relevant code
Perpetual licensing is available if your team prefers a one-time purchase
Cons
CPU tracing adds more overhead than sampling and may not be suitable for production on latency-sensitive systems
Advanced features and support vary by licensing tier, so some capabilities require the higher-priced Advanced tier
3. JProfiler
JProfiler is a commercial Java profiler from ej-technologies that combines high-level analytics with low-level JVM data. It covers CPU, memory, thread, and database query profiling in one tool. The visual UI renders call trees and allocation graphs, making complex profiling data easier to navigate.
A standout feature is its database profiling layer. It traces JDBC calls, JPA queries, and NoSQL operations like MongoDB calls back to the originating Java code. So you don’t have to manually correlate slow queries to methods.
Key features
JDBC/JPA/NoSQL query profiling: Trace database calls back to the Java methods that triggered them, with timing data per query
Heap walker with reference chains: Navigate the object graph visually and trace why specific objects aren’t being garbage collected
Request tracking for JEE and Spring: Follow a request through servlets, EJBs, and Spring components to see where time goes
Trigger system for automated snapshots: Set conditions like “CPU exceeds 90% for 10 seconds” and capture a snapshot automatically
Pricing
Single-user license: $768 (with support)
Single-user license with 1 year of support and upgrades: $768
Floating license with 1 year of support and upgrades: $3,078
Pros
Database query profiling connects slow queries directly to the Java code that generates them
Visual heap walker makes memory leak investigation easier by showing reference chains to garbage collector roots
Cons
Profiling can add noticeable CPU and memory overhead, particularly when using allocation recording or heap snapshots
Its extensive profiling capabilities can make it more complex to configure and use than simpler Java profilers
4. async-profiler
async-profiler is an open-source sampling profiler for HotSpot JVMs. It uses HotSpot-specific APIs like AsyncGetCallTrace alongside Linux perf_events to capture accurate CPU profiles with low overhead. It can also profile Java heap allocations, native memory, contended locks, and hardware and software performance counters.
Many Java profilers sample thread stacks at JVM safepoints, so they can miss code running between safepoints. async-profiler doesn’t have that limitation. It collects stack traces asynchronously, so it can capture code running between safepoints.
Key features
Safepoint-free CPU profiling: Sample call stacks without waiting for JVM safepoints, eliminating the bias that often distorts other profilers’ results
Allocation profiling: Track Java heap allocations by method without the overhead of full instrumentation
Lock contention profiling: Capture Java monitor and ReentrantLock contention events to find concurrency bottlenecks
Flame graph output: Generate interactive flame graphs directly from profiling data for fast visual analysis of CPU hotspots
Pricing
Free and open source (Apache 2.0 license)
Pros
Low-overhead sampling makes it suitable for production profiling on latency-sensitive systems
Safepoint-free sampling avoids the safepoint bias that can skew CPU profiles
Cons
Linux-only for full perf_events integration, which limits use on macOS and Windows dev machines
Command-line interface with no built-in GUI, and flame graphs are generated as HTML files you open in a browser or another viewer
5. Eclipse MAT
Eclipse Memory Analyzer Tool (MAT) is a free, open-source tool purpose-built for analyzing Java heap dumps. It can analyze very large heap dumps and help identify objects responsible for excessive memory retention.
MAT’s Leak Suspects report is the standout feature. It analyzes the heap dump and identifies potential leak suspects based on retained memory, along with reference chains showing why those objects remain reachable. If you’re investigating an OutOfMemoryError in production, this can help narrow down the likely cause.
Key features
Automatic leak suspects report: Identify potential memory leak suspects and see the reference chains keeping them reachable
Dominator tree analysis: See which objects retain the most heap memory, ranked by retained size
OQL (Object Query Language): Query the heap dump like a database to find specific objects or memory-retention patterns
Comparison of heap snapshots: Compare two heap dumps to see what changed between them and help isolate memory growth over time
Pricing
Free and open source (Eclipse Public License 2.0)
Pros
Designed to handle heap dumps with hundreds of millions of objects
Leak Suspects report delivers actionable results without requiring deep GC internals knowledge
Cons:
Only analyzes heap dumps, so you’ll need a separate tool for CPU profiling and thread analysis
No live profiling, so you’ve got to capture the heap dump first, then open it in MAT
6. IntelliJ Profiler
IntelliJ Profiler is built into IntelliJ IDEA Ultimate. It combines JDK Flight Recorder with async-profiler, giving you CPU and memory profiling directly inside the IDE. You won’t need to install a separate profiler or configure a profiling agent.
IntelliJ Profiler renders flame graphs, call trees, and method lists alongside your source code. You can select a hotspot in the flame graph and navigate directly to the corresponding source code, keeping the investigation closely connected to the code you’re profiling.
Key features
Zero-configuration profiling: Start profiling a Java process from IntelliJ IDEA without installing or configuring a separate profiling tool
Flame graph with source navigation: Select a frame in the flame graph and jump directly to the corresponding source code
Allocation tracking: See which methods allocate the most objects and navigate directly to the code responsible
Snapshot comparison: Compare profiling snapshots to identify changes in CPU usage, allocations, and other profiling data
Pricing
Included with IntelliJ IDEA Ultimate.
Pros
Profiling is a built-in feature, so there’s nothing to install or configure
Source-level navigation from flame graphs eliminates the “find the code” step that slows standalone profilers down
Cons
Requires IntelliJ IDEA Ultimate
It’s primarily designed for development workflows, so teams needing dedicated production profiling and continuous runtime monitoring will need additional tools
7. Datadog Continuous Profiler
Datadog Continuous Profiler runs continuously in production and sends profiling data through the Datadog Agent to the Datadog platform. It captures CPU, memory, lock, wall-time, disk I/O, and other profile types, giving you code-level visibility across the services where profiling is enabled.
The value is in the “always-on” part. When a latency spike hits production at 3 AM, Datadog already has profiling data from that period. You don’t need to reproduce the issue first. And because Continuous Profiler integrates with Datadog APM, you can correlate profiling data with distributed requests to investigate which parts of your code are consuming resources.
Key features
Always-on production profiling: Capture CPU, memory, and contention data continuously without manually starting a profiling session
Trace-to-profile correlation: Correlate profiling data with distributed requests to investigate which code is contributing to request latency
Cross-service profiling: Aggregate profiling data across distributed Java services to find bottlenecks spanning microservices
Code-level performance insights: See which methods drive the most infrastructure cost across your Java fleet
Pricing
Continuous Profiler: $19/host/month when billed annually; $23/host/month when billed monthly or on demand
Continuous Profiler – Containers: $2/profiled container/month when billed annually or monthly
APM Pro: $35/host/month when billed annually; $42/host/month when billed monthly or on demand
APM Enterprise (includes Continuous Profiler): $40/host/month when billed annually; $48/host/month when billed monthly or on demand
Pros
Always-on profiling means you’ve got the data before you know you need it, which kills the “reproduce the issue” cycle
Trace-to-profile linking connects slow requests to the code responsible, across distributed services
Cons
Costs scale with host count, so a large Java fleet runs up a significant monthly bill
8. New Relic APM
New Relic APM provides Java application performance monitoring as part of a broader observability platform. It captures transaction traces, error analytics, and JVM metrics such as heap usage, garbage collection, and thread activity through a Java agent. Its strength is correlating Java performance data with infrastructure metrics, logs, and external service calls.
New Relic’s thread profiler captures periodic snapshots of thread stacks and visualizes them as a call tree. It isn’t a dedicated Java profiler like YourKit or JProfiler, but for triaging production issues alongside other telemetry, having the data in one platform view saves time.
Key features
Transaction tracing: Break down response time by method, database call, and external service within each transaction
JVM metrics dashboard: Monitor heap usage, GC frequency and duration, thread count, and class loading in real time
Distributed tracing: Follow a request through multiple Java microservices and see where each one adds latency
Error analytics with stack traces: Group errors by type and investigate stack traces associated with individual errors
Pricing
New Relic uses usage-based pricing across four editions: Free, Standard, Pro, and Enterprise.
Free: $0, including 100 GB of data ingest/month, one full platform user, and unlimited basic users
Standard: $10/month for the first full platform user and $99/month for each additional full platform user, up to five users
Pro: $349/user/month with an annual commitment or $418.80/user/month with monthly pay-as-you-go
Enterprise: Custom pricing
Core users: $49/user/month on Standard, Pro, and Enterprise
Original data ingest: $0.40/GB beyond the free 100 GB/month
Data Plus: $0.60/GB beyond the free 100 GB/month
EU data center storage: Additional $0.05/GB/month
Pros
One platform for traces, metrics, logs, and application performance data reduces tool sprawl for teams already using New Relic
The free tier provides 100 GB of data ingest per month and one full platform user, making it possible to evaluate the platform without an upfront subscription
Cons
Usage-based pricing makes monthly costs hard to predict, especially with large volumes of trace data
9. VisualVM
VisualVM is a free, open-source visual tool for monitoring and profiling JVMs. It was distributed with the JDK before becoming a standalone download. It covers CPU profiling, memory profiling, thread monitoring, heap dumps, and JMX-based metrics in a clean GUI.
VisualVM is a practical starting point when your budget is zero. Its plugin system extends it with tools like an MBeans browser, thread inspector, and Visual GC.
Key features
CPU and memory profiling: Profile CPU usage and memory allocations through sampling and instrumentation modes
Thread analysis with deadlock detection: Visualize thread states and detect deadlocked threads automatically
Heap dump analysis: Capture and analyze heap dumps with object count, size, and reference information
Plugin ecosystem: Extend functionality through plugins for GC visualization, MBeans browsing, and more
Pricing
Free and open source (GPLv2 with Classpath Exception)
Pros
Completely free with no license restrictions, so it’s accessible to any team regardless of budget
Covers CPU, memory, threads, and heap dumps in one tool, so you don’t need to learn multiple tools
Cons
Instrumentation profiling adds noticeable overhead, so use it with care in production on performance-sensitive systems
No built-in GC log analysis. You’ll need a separate tool like Azul’s GC Log Analyzer to diagnose GC behavior
How to Choose the Right Java Profiling Tool
Choose based on what you’re trying to diagnose, where you’re profiling, and how much overhead you can tolerate:
If your biggest problem is GC pauses and latency on production Java, start with Azul. Mission Control and GC Log Analyzer are purpose-built for JVM monitoring, profiling, and GC analysis. And Azul Prime’s C4 collector eliminates the pauses entirely.
If you need deep, interactive profiling during development, YourKit and JProfiler both provide detailed CPU, memory, and thread profiling. YourKit provides granular memory allocation analysis, while JProfiler emphasizes database query tracing for JEE and Spring apps.
If you need always-on profiling across a distributed Java fleet, Datadog Continuous Profiler or New Relic APM integrate profiling into your observability stack. Datadog’s trace-to-profile linking is especially useful for connecting application traces to profiling data.
If budget’s the primary constraint, async-profiler provides low-overhead CPU profiling for free, Eclipse MAT handles heap dump analysis at no cost, and VisualVM covers JVM monitoring and profiling through a GUI.
If you want to profile without leaving your IDE, IntelliJ Profiler provides CPU and memory profiling directly inside IntelliJ IDEA with no separate profiler setup. It’s primarily designed for development workflows, though.
Find the Bottleneck Before it Finds You
Every Java performance issue has a cause, and a profiling tool helps you see it.
For many enterprise Java apps, garbage collection is a common bottleneck. Azul’s profiling tools show you what the collector’s doing. And if the collector’s the problem, Azul Prime replaces it with one that doesn’t pause.
Talk to Azul’s Java experts about your performance challenge so you can find the cause and fix it at the source.
FAQs
1. What Is the Best Java Profiling Tool for Production Use?
async-profiler is a popular option for production CPU profiling because it uses low-overhead sampling. Teams on Azul Core or Azul Prime can also use Mission Control with JFR for low-overhead, production-safe profiling and deeper GC and JVM diagnostics.
2. Is VisualVM Good Enough for Enterprise Java Profiling?
VisualVM works well for dev-time profiling and basic JVM monitoring, but it needs care in production because its instrumentation mode can add significant overhead, and it has no built-in GC log analysis. Many enterprises pair it with a dedicated GC analyzer or production profiler.
3. What Is the Difference Between Sampling and Instrumentation Profiling?
Sampling profilers take periodic snapshots of the call stack at fixed intervals. They show where the JVM spends the most time and have minimal overhead. Instrumentation profilers inject bytecode to track every method entry and exit. You’ll get exact call counts, but you’ll also add measurable overhead. Use sampling for production and instrumentation for deep debugging.
4. How Much Overhead Do Java Profilers Add?
It depends heavily on the profiler, profiling mode, and amount of data being collected. Sampling generally has lower overhead than instrumentation or tracing. JFR-based tools such as Azul Mission Control are designed for low-overhead profiling, while tools such as YourKit let you adjust the amount of data collected to control overhead.
5. Can You Use Multiple Java Profiling Tools Together?
Yes, and that’s what many enterprise teams do. You might use async-profiler or JFR for production CPU and JVM profiling, Eclipse MAT for heap dump analysis, and YourKit or JProfiler for deeper application profiling during development. Azul’s stack combines production JVM monitoring through Mission Control with dedicated GC log analysis through GC Log Analyzer.
