Java garbage collection has evolved from simple stop-the-world collectors into a range of sophisticated options designed for different performance goals. Some collectors maximize raw throughput, others reduce pause times, and newer low-latency collectors aim to keep applications responsive even with very large heaps.
Choosing the right garbage collector depends on workload shape, heap size, latency targets, deployment environment, and operational tolerance for tuning. A batch job, a high-traffic web service, a real-time-ish trading platform, and a memory-heavy analytics system may all benefit from different JVM GC strategies.
| # | Preview | Product | Price | |
|---|---|---|---|---|
| 1 |
|
Java Performance: In-Depth Advice for Tuning and Programming Java 8, 11, and Beyond | $38.58 | Buy on Amazon |
| 2 |
|
Java Performance Tuning (2nd Edition) | $19.60 | Buy on Amazon |
| 3 |
|
Java Performance Tuning | $11.48 | Buy on Amazon |
| 4 |
|
Sun Performance and Tuning: Java and the Internet (2nd Edition) | $59.68 | Buy on Amazon |
| 5 |
|
High-Performance Java Persistence | $40.71 | Buy on Amazon |
As an Amazon Associate I earn from qualifying purchases.
Modern Java makes the default choice reasonable for many applications, but understanding Serial, Parallel, G1, ZGC, Shenandoah, and legacy options like CMS helps teams make better trade-offs. The goal is not to find a universally best collector, but to match pause behavior, throughput, and tuning complexity to the application’s actual needs.
How Java Garbage Collection Works
Java garbage collection is the JVM’s automatic memory management system. Instead of requiring developers to explicitly free objects, the JVM tracks which objects are still reachable by a running program and reclaims memory from objects that can no longer be reached. This happens inside the Java heap, where most application objects are allocated. The collector’s job is to keep enough free heap space available while minimizing the cost of collection work on application threads.
#1 Best Overall
Most JVM collectors rely on the idea of reachability. Objects referenced from active thread stacks, static fields, JNI references, and other JVM-managed roots are considered live. The collector follows references from these roots to find the live object graph. Anything outside that graph is eligible for reclamation. This model is safe because the JVM does not free memory simply because an object “looks unused”; it frees memory only when the object cannot be reached by any valid execution path.
Generational collection
Many Java collectors use a generational heap because most objects die young. Temporary objects created during request handling, JSON parsing, stream operations, string manipulation, or short-lived collections often become unreachable quickly. To take advantage of this pattern, the heap is commonly divided into a young generation and an old generation. New objects are usually allocated in the young generation. If they survive enough young collections, they may be promoted to the old generation, where longer-lived application state, caches, and session data tend to reside.
- Young collections reclaim short-lived objects and are usually frequent. They are often smaller and faster because they scan a limited area of the heap.
- Old or mixed collections deal with long-lived objects and larger heap regions. They are typically more expensive and more relevant to latency-sensitive applications.
- Full collections are broad, disruptive events that may compact much or all of the heap. Modern collectors try to avoid them during normal operation.
Pauses, concurrency, and compaction
Garbage collection competes with application work for CPU time and memory bandwidth. Some phases require a stop-the-world pause, where application threads are briefly suspended so the JVM can safely inspect or update object references. Other phases may run concurrently with the application, reducing visible pause time at the cost of extra background CPU usage. The balance between paused work and concurrent work is one of the main differences between collectors such as Parallel GC, G1, ZGC, and Shenandoah.
Recommended Free Tools
Another core activity is compaction. As objects are allocated and reclaimed, free memory can become fragmented. A compacting collector moves live objects together so larger contiguous areas become available for future allocation. This improves allocation speed and reduces fragmentation risk, but moving objects requires updating references and coordinating with running threads. Traditional collectors often perform more compaction during pauses, while newer low-latency collectors use barriers and concurrent relocation techniques to keep pauses short even on large heaps.
What GC metrics actually mean
When comparing collectors, three measurements matter most: throughput, latency, and footprint. Throughput describes how much total time is spent running application code instead of GC work. Latency focuses on pause duration and response-time outliers, such as p99 or p99.9 request times. Footprint includes heap size, native memory, and CPU overhead needed by the collector. A batch analytics job may prefer maximum throughput even if occasional pauses are long, while a trading system, API gateway, or interactive service may accept more CPU overhead to keep pauses consistently low.
Serial and Parallel Garbage Collectors
The Serial and Parallel garbage collectors are the traditional stop-the-world collectors in the JVM. They are simple, mature, and still useful in the right environments. Both collectors pause application threads during collection, but they differ in how much CPU parallelism they use. The Serial collector performs garbage collection work with a single thread, while the Parallel collector uses mulle GC threads to speed up collection on multi-core machines.
Serial Garbage Collector
The Serial collector is enabled with -XX:+UseSerialGC. It uses a single thread for both young-generation and old-generation collection. During a collection pause, all application threads stop, the collector reclaims memory, and then the application continues. This makes its pause behavior straightforward, but pauses can become long when the heap grows or when the old generation needs to be compacted.
Serial GC is best suited for small heaps, single-core environments, command-line tools, short-lived batch utilities, small containers, and applications where memory footprint matters more than pause time. Because it uses only one GC thread, it avoids the overhead of coordinating mulle collector threads. On a small JVM with a heap of a few hundred megabytes, this simplicity can be an advantage. On a server handling interactive traffic, however, Serial GC is usually a poor fit because a full collection can block every request-handling thread for a noticeable period.
Parallel Garbage Collector
The Parallel collector, enabled with -XX:+UseParallelGC, is designed for high throughput. Like Serial GC, it uses stop-the-world pauses, but it performs collection work with mulle threads. Young-generation collections are parallelized, and old-generation collections can also be parallelized and compacting. This allows the JVM to reclaim memory faster on machines with several CPU cores, reducing the wall-clock duration of many pauses compared with Serial GC.
Rank #2
- Used Book in Good Condition
Parallel GC is a good match for workloads where total work completed per unit of time matters more than consistently low pause latency. Examples include batch processing, report generation, ETL jobs, build systems, simulations, offline analytics, and backend services that can tolerate occasional longer pauses. It often delivers strong throughput because it allows application threads to run with relatively low concurrent GC overhead; when collection is needed, the JVM stops the application, uses available CPU cores aggressively, and then returns control to the program.
| Collector | Main Strength | Pause Behavior | Best Fit |
|---|---|---|---|
| Serial GC | Low overhead and simplicity | Single-threaded stop-the-world pauses | Small heaps, simple tools, constrained runtimes |
| Parallel GC | High throughput | Multi-threaded stop-the-world pauses | Batch jobs and CPU-rich non-latency-sensitive services |
Tuning for these collectors is usually less complex than tuning low-latency collectors, but a few options are common. Heap sizing with -Xms and -Xmx has a large impact: a larger heap can reduce collection frequency but increase worst-case pause duration. For Parallel GC, -XX:ParallelGCThreads controls how many threads participate in collection. The flags -XX:MaxGCPauseMillis and -XX:GCTimeRatio can express pause and throughput goals, though they are goals rather than strict guarantees.
The Tool Desk
Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →In modern Java applications, Serial GC is typically a niche choice and Parallel GC is a throughput-oriented choice. If an application runs in a tiny container, starts often, and has modest memory needs, Serial GC can be perfectly adequate. If an application performs heavy computation or large batch operations and users are not waiting on individual low-latency responses, Parallel GC remains a practical option. For APIs, trading platforms, user-facing web applications, and systems with tight response-time targets, collectors such as G1, ZGC, or Shenandoah are usually better candidates.
G1 Garbage Collector
The Garbage-First collector, commonly called G1, is the default garbage collector for many modern JVM releases and is designed as a balanced option between high throughput and predictable pause times. Unlike Serial and Parallel GC, which treat the heap as broad young and old generations, G1 divides the heap into many equally sized regions. Each region can be used for young objects, old objects, or very large “humongous” allocations. This regional layout lets G1 collect selected parts of the heap instead of always compacting an entire generation at once.
G1 is a generational, mostly concurrent, compacting collector. It still performs stop-the-world pauses, but it tries to keep them within a configurable pause-time goal using -XX:MaxGCPauseMillis. During young collections, G1 evacuates live objects from young regions into survivor or old regions. As the heap fills, it also performs concurrent marking to identify old regions with the most reclaimable space. Later, during mixed collections, it collects young regions together with selected old regions that contain a large amount of garbage. This is where the name “Garbage-First” comes from: the collector prioritizes regions that are expected to free the most memory for the least pause cost.
Where G1 Fits Best
G1 is well suited for server-side applications with medium to large heaps, especially services where long full-GC pauses are unacceptable but maximum raw throughput is not the only goal. Typical examples include REST APIs, Spring Boot services, application servers, stream-processing workers, and enterprise backends running with heaps from a few gigabytes to dozens of gigabytes. It is often a strong default for containerized Java workloads because it behaves reasonably well without extensive tuning and adapts to changing allocation patterns better than older collectors.
Quick wins for a faster PC:
Clear out junk files and repair common Windows errorsFree Scan →Scan for outdated or missing drivers - takes under a minuteDriver Scan →| Characteristic | G1 Behavior |
|---|---|
| Throughput | Good, though usually below Parallel GC for pure batch workloads |
| Latency | Moderate to good, with pause-time goals rather than strict guarantees |
| Pause pattern | Frequent shorter pauses, plus occasional longer pauses under pressure |
| Heap size fit | Works well for multi-gigabyte heaps and general server applications |
| Tuning complexity | Moderate; often usable with defaults, but tunable for pause targets |
In practice, G1’s most common tuning option is the pause target. For example, lowering -XX:MaxGCPauseMillis asks G1 to perform smaller collections more often, which may reduce individual pause duration but can also increase CPU overhead and reduce application throughput. Raising the target allows larger collection sets and may improve throughput at the cost of longer pauses. Heap sizing also matters: if the heap is too small, G1 has less room to perform concurrent work and may fall back to expensive full collections. A healthy G1 configuration usually leaves enough headroom for allocation bursts and concurrent marking to finish before memory pressure becomes severe.
G1 is not the best fit for every application. For short-lived command-line tools or tiny heaps, Serial GC can be simpler and faster. For CPU-bound batch jobs that care mostly about total completion time, Parallel GC may deliver better throughput. For systems with strict sub-10-millisecond or sub-millisecond pause requirements, ZGC or Shenandoah are often better candidates. Still, for many production Java services, G1 offers a practical compromise: manageable pauses, solid throughput, compaction to reduce fragmentation, and far less tuning burden than older low-pause collectors such as CMS.
ZGC and Shenandoah for Low-Latency Applications
ZGC and Shenandoah are designed for applications where long garbage collection pauses are unacceptable. Unlike throughput-oriented collectors that may stop application threads for longer compaction or evacuation phases, these collectors move most GC work to concurrent phases that run while the application continues executing. The goal is not to maximize raw throughput at all costs, but to keep pause times consistently low, even as heap sizes grow into tens or hundreds of gigabytes.
Rank #3
ZGC, available as a production collector in modern OpenJDK releases, is built around concurrent marking, relocation, and reference processing. It uses colored pointers and load barriers so application threads can safely access objects while the collector relocates them. In practice, ZGC aims for pause times in the low milliseconds, often below 10 ms, because stop-the-world pauses are limited to small coordination phases rather than full heap processing. It is a strong fit for latency-sensitive services such as trading platforms, interactive APIs, ad serving systems, gaming backends, and large in-memory applications where predictable response time matters more than maximum throughput.
Shenandoah follows a similar low-pause philosophy, but uses Brooks-style forwarding pointers and barriers to allow concurrent evacuation and compaction. It was developed in the OpenJDK ecosystem and is available in several JDK distributions. Like ZGC, Shenandoah keeps pause times mostly independent of heap size by avoiding long stop-the-world compaction. It can be attractive for services that experience frequent allocation bursts, run with large heaps, or need smoother latency than G1 can provide under pressure. Shenandoah also offers tuning options such as heuristic selection, pacing, and allocation headroom controls, which can help adapt it to specific application behavior.
| Collector | Main Strength | Pause Behavior | Best Suited For |
|---|---|---|---|
| ZGC | Very low pauses with large heaps | Mostly concurrent, typically sub-10 ms pauses | Large-scale latency-sensitive services and memory-heavy applications |
| Shenandoah | Concurrent compaction with flexible heuristics | Short pauses mostly independent of heap size | Low-latency services with allocation bursts or strict response-time targets |
The trade-off is that both collectors usually consume more CPU than simpler collectors because barriers, concurrent marking, and concurrent relocation add ongoing work while application threads run. They may also deliver slightly lower peak throughput than Parallel GC or a well-tuned G1 configuration in batch workloads. For example, an offline report generator, ETL job, or build process may finish faster with Parallel GC because short pauses are less valuable than total completion time. By contrast, a customer-facing service with strict percentile latency targets, such as p99 or p99.9 response times, may benefit significantly from ZGC or Shenandoah.
For practical selection, start with ZGC when running a modern JDK and the application has a large heap, strict latency goals, or unpredictable pause spikes under G1. Consider Shenandoah when your JDK distribution supports it well and you want another mature low-latency option with configurable heuristics. In both cases, validate with production-like load tests rather than relying only on average pause time. Watch allocation rate, CPU headroom, live data size, tail latency, and GC logs. These collectors are powerful, but they work best when the system has enough spare CPU to let concurrent GC keep up without falling behind during traffic spikes.
CMS and Legacy Garbage Collection Options
The Concurrent Mark-Sweep collector, usually called CMS, was one of the first mainstream JVM collectors designed to reduce long old-generation pauses. Instead of waiting until the old generation filled and then compacting the heap in a single stop-the-world event, CMS performed most of its marking work concurrently with the application. This made it attractive for older server-side Java applications that needed better responsiveness than the Parallel collector could provide, especially web applications, trading systems, and latency-sensitive services running before G1 became the default.
Free tools Windows power users keep installed
One-click scans. No signup required.
CMS split old-generation collection into several phases. Initial marking and remarking still stopped application threads, but the longer concurrent mark and sweep phases ran while the application continued executing. This reduced many pause times compared with fully stop-the-world collectors, but it came with trade-offs. CMS did not compact the old generation during normal collection, so memory fragmentation could build up over time. If the JVM could not find enough contiguous free space for an allocation, it could fall back to a full GC, causing a much longer pause than the application normally experienced.
Where CMS fit historically
CMS was best suited for applications with moderately large heaps, stable allocation patterns, and a clear need for shorter old-generation pauses. It often required careful sizing of the young generation, survivor spaces, and old-generation occupancy thresholds. Starting CMS too late increased the chance of concurrent mode failure; starting it too early consumed CPU and reduced throughput. This made CMS more tuning-intensive than G1 for many teams, particularly when workloads had bursty allocation rates or unpredictable live-data sizes.
| Collector | Status | Main characteristic | Typical use today |
|---|---|---|---|
| CMS | Removed in modern JDKs | Concurrent old-generation marking and sweeping, no regular compaction | Only legacy JVM deployments that cannot upgrade immediately |
| Incremental CMS | Obsolete | Attempted to reduce CPU impact on single or dual-core systems | Avoid; replaced by modern collectors and hardware assumptions |
| PermGen-era collectors | Legacy | Managed class metadata in permanent generation before Metaspace | Relevant only when maintaining Java 7 or older applications |
| Explicit full-GC-heavy setups | Discouraged | Relied on manual calls or scheduled full collections | Replace with collector tuning and allocation fixes |
For modern Java versions, CMS is mainly useful as historical context. It was deprecated in JDK 9 and removed in JDK 14, so applications moving to current long-term-support releases cannot rely on it. G1 replaced CMS for many general-purpose server workloads because it provides incremental compaction, predictable pause-time goals, and easier ergonomics. For applications that originally chose CMS to control latency, G1 is often the first migration target; for stricter pause requirements, ZGC or Shenandoah are usually better candidates.
Legacy GC choices also matter when maintaining older JVMs in production. Java 6, Java 7, and early Java 8 deployments may still expose behavior around PermGen sizing, class unloading, promotion failures, and full-GC compaction that does not map directly to newer releases. In these environments, practical operation often means monitoring old-generation occupancy, promotion rates, fragmentation indicators, and full-GC frequency. If full GCs appear after long CMS cycles, the application may need a larger heap, earlier CMS initiation, reduced allocation pressure, or an upgrade plan rather than more flags layered onto an aging configuration.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsIn new systems, CMS and related legacy options should generally be avoided. Their tuning model assumes older JVM internals and older hardware patterns, and the operational risk of rare but severe pauses is difficult to justify when G1, ZGC, and Shenandoah are available. CMS remains valuable to understand because many GC logs, performance guides, and production incidents were shaped by it, but it is no longer the default answer for low-pause Java services.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Comparing Java Garbage Collectors by Use Case
Choosing a Java garbage collector is less about finding the universally “best” option and more about matching collector behavior to application goals. A batch processing job that runs overnight may care most about total completion time, while a trading service, API gateway, or mullayer game server may care far more about keeping pauses consistently short. Heap size, allocation rate, CPU availability, container limits, and service-level objectives all affect the right choice.
| Use case | Recommended collector | Best fit | Main trade-off |
|---|---|---|---|
| Small command-line tools, simple utilities, test runners | Serial GC | Minimal overhead and simple behavior on small heaps | Stop-the-world pauses grow quickly as heap size increases |
| Batch jobs, ETL pipelines, CPU-heavy backend workers | Parallel GC | High throughput and efficient use of multiple cores | Longer pauses compared with modern low-latency collectors |
| General-purpose web services and microservices | G1 GC | Balanced throughput, predictable pauses, good default behavior | May need tuning for strict latency targets or very large heaps |
| Latency-sensitive APIs, trading systems, interactive services | ZGC or Shenandoah | Very short pause times, often independent of heap size | Higher CPU and memory overhead than throughput-oriented collectors |
| Legacy Java applications on older JVMs | CMS, if already deployed | Lower pauses than old Parallel GC in pre-G1 environments | Deprecated or removed in modern JVMs; migration is preferred |
For throughput-oriented workloads, Parallel GC is often still a strong candidate. It uses mulle threads for collection and prioritizes doing as much application work as possible over time. This works well for offline computation, report generation, indexing jobs, image processing, and other workloads where a one-second or multi-second pause is acceptable if overall job duration improves. In contrast, Serial GC is mainly useful for very small heaps, single-core environments, short-lived tools, or constrained containers where the simplicity of one collector thread is an advantage.
G1 is the usual starting point for modern server-side Java. It splits the heap into regions and tries to meet a pause-time goal while maintaining good throughput. For many REST APIs, Spring Boot services, Kafka consumers, and medium-to-large enterprise applications, G1 offers the best balance without requiring deep tuning. Its pause behavior is usually much better than Parallel GC for interactive systems, although it may not match ZGC or Shenandoah when applications require consistently tiny pauses under heavy allocation pressure.
ZGC and Shenandoah are best suited for applications where pause duration is a product concern, not just an operational metric. They perform most collection work concurrently with the application, which keeps stop-the-world pauses very short even with large heaps. This makes them attractive for systems with hundreds of gigabytes of memory, real-time user interaction, strict tail-latency targets, or workloads where a long pause can trigger timeouts, failovers, or visible user disruption. The cost is that they may consume more CPU, require extra memory headroom, and deliver slightly lower peak throughput than Parallel GC or a well-behaved G1 configuration.
A practical comparison should include production-like load testing rather than relying only on defaults. Measure average latency, p95 and p99 latency, maximum pause time, CPU usage, allocation rate, live heap after collection, and container memory pressure. If the application has no strict latency target, start with G1 and compare Parallel GC for throughput-heavy jobs. If p99 latency or pause outliers dominate the problem, test ZGC or Shenandoah early. For older CMS deployments, the safest path is usually to benchmark migration to G1 first, then evaluate ZGC or Shenandoah if pause goals remain difficult to meet.
How to Choose the Right Garbage Collector
Choosing a Java garbage collector should start with service objectives rather than collector features. Define the maximum acceptable pause time, required throughput, heap size, allocation rate, CPU budget, and deployment environment before changing JVM flags. A batch job that can tolerate multi-second pauses has very different needs from an API gateway that must keep p99 latency below 50 ms. The best collector is the one that meets those targets with the least operational risk.
For many modern server applications, G1 GC is the safest default. It is the default collector in recent HotSpot JVMs because it offers a practical balance between throughput and predictable pauses. G1 works well for web services, microservices, and moderate-to-large heaps where occasional pauses are acceptable but long full-GC events are not. Start with a fixed or well-sized heap, set a pause goal such as -XX:MaxGCPauseMillis=200 only if needed, and avoid excessive tuning until production metrics show a problem.
Outdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchWindows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallIf throughput matters more than latency, consider the Parallel GC. It is often a strong choice for offline processing, ETL jobs, simulations, report generation, and workloads where finishing total work quickly is more than keeping pauses short. Parallel GC uses multiple threads for collection and can deliver excellent CPU efficiency, but pause times may be longer as heap size grows. For very small applications, command-line tools, short-lived processes, or constrained single-core environments, the Serial GC may still be appropriate because of its low overhead and simple behavior.
Best Value
For applications with strict latency requirements, evaluate ZGC or Shenandoah. These collectors are designed to keep pauses very short, often in the low-millisecond range, even with large heaps. They are good fits for trading platforms, real-time APIs, interactive SaaS products, large caches, and services where tail latency is a business metric. The trade-off is that concurrent collection consumes CPU while the application is running, so capacity planning must include extra headroom. ZGC is a particularly strong option on current JDK releases when very large heaps and low pauses are required.
| Workload | Best starting choice | Main consideration |
|---|---|---|
| General web service or microservice | G1 GC | Balanced latency and throughput |
| Batch processing or data pipeline | Parallel GC | Maximum throughput, longer pauses acceptable |
| Small CLI tool or tiny service | Serial GC | Low overhead and simplicity |
| Large heap with tight p99 latency | ZGC or Shenandoah | Short pauses with extra CPU overhead |
| Older Java runtime | G1 GC, or CMS only if required | Upgrade path and support status |
Selection should also account for Java version. On current LTS releases such as Java 17 and Java 21, G1 and ZGC are mature production options, while Shenandoah availability depends on the JDK distribution. CMS should generally be avoided for new deployments because it has been removed from modern HotSpot releases. If an application still depends on CMS behavior, treat that as a migration signal and test G1 or a low-latency collector under realistic traffic.
Validate the decision with measurements from the actual workload. Enable GC logging, observe allocation rate, pause percentiles, heap occupancy after collection, CPU usage, and full-GC frequency. Load tests should include warm-up, peak traffic, failure recovery, and realistic object churn. Change one variable at a time: collector first, then heap sizing, then pause targets or advanced flags. In most cases, the practical path is simple: start with G1, move to Parallel GC for throughput-heavy jobs, and move to ZGC or Shenandoah when tail latency requirements justify the additional CPU cost.
What’s actually slowing this PC down?
Pick the symptom - the matching free tool is one click away.
Frequently Asked Questions
Which Java garbage collector should I use by default?
For most modern server-side Java applications, G1 GC is the safest default choice. It offers a good balance between throughput and pause-time control, and it is the default collector in many recent JDK versions. If your application has strict low-latency requirements, evaluate ZGC or Shenandoah instead.
When should I choose ZGC or Shenandoah over G1?
Choose ZGC or Shenandoah when long GC pauses are unacceptable, such as in trading systems, real-time APIs, interactive services, or applications with very large heaps. These collectors are designed to keep pause times very low, often in the millisecond range, even with large memory sizes. The tradeoff can be slightly higher CPU usage and the need to run on a JDK version where the collector is mature and supported.
Is the Parallel GC still useful for modern Java applications?
Yes, Parallel GC can still be a strong choice for batch jobs, data processing, command-line tools, and workloads where total throughput matters more than pause time. It uses mulle threads to speed up collection but can still produce longer stop-the-world pauses. If users are not waiting on individual requests, those pauses may be acceptable.
Should I still use CMS in new Java applications?
No, CMS should generally be avoided for new applications because it has been deprecated and removed from newer JDK releases. It was designed to reduce old-generation pauses, but G1, ZGC, and Shenandoah are better modern options. If you are maintaining an older system that still uses CMS, plan a migration and test pause behavior carefully before changing collectors.
The Tool Desk
Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →How do I know if my garbage collector is causing performance problems?
Enable GC logging and look for frequent collections, long stop-the-world pauses, high allocation rates, or repeated full GCs. Also compare application metrics such as request latency, CPU usage, heap occupancy, and throughput during GC events. If latency spikes line up with GC pauses, you may need to adjust heap sizing, reduce allocation pressure, or switch collectors.
Bottom Line
Java gives you several garbage collector choices because applications optimize for different outcomes: raw throughput, predictable latency, small footprint, or minimal tuning. For most modern services, G1 is the safest default, while ZGC and Shenandoah are better fits when low pause times matter more than maximum throughput.
If you are unsure where to start, use the JVM default, measure with realistic traffic, and change collectors only when you have a clear performance goal. Match the GC to your workload, monitor pause times, allocation rate, heap usage, and CPU cost, then tune only as much as the evidence requires.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
Free tools Windows power users keep installed
One-click scans. No signup required.
