JOptimize is an AI-powered Java performance analyzer that automatically detects memory leaks, N+1 queries, security vulnerabilities, and concurrency issues before they hit production.
JOptimize Team
Problem: 47% of Java applications have memory leaks or performance issues that developers discover only in production or load testing - after weeks of work and thousands in cloud costs.
Root cause: Manual code review for performance anti-patterns is tedious, error-prone, and doesn't scale.
Solution: JOptimize is a SaaS Java performance analyzer that scans your codebase in seconds and detects 50+ performance and security anti-patterns automatically.
N+1 Query Problem
findById() or query() called inside loopsConnection Pool Exhaustion
Unbounded Queries
findAll() without .limit() or paginationEager Fetching Overhead
@ManyToOne(fetch = EAGER) loading unnecessary dataMissing Database Indexes
String Concatenation in Loops
for (int i = 0; i < 1000000; i++) { str = str + "data"; // Allocates 1MB per iteration }
Large Object Allocations
Streams Not Closed
new FileInputStream() without try-with-resourcesStatic Collections Growing Without Bounds
static List accumulating objectsThread Creation in Hot Path
new Thread() in request handlersSynchronized Methods
Mutable Static Fields
Blocking Operations in CompletableFuture
.get() or .join() on ForkJoinPoolMissing @Transactional Annotation
Spring Async Misuse
@Async without thread pool configurationObjectMapper Instantiation in Loop
new ObjectMapper() inside JSON serialization loopController Business Logic
Hardcoded API Keys & Passwords
password = "secret123" in codeSQL Injection Vectors
Weak Cryptography
MD5, SHA-1, DES algorithmsSensitive Data in Logs
logger.debug("credit card: " + ccNumber)Hardcoded JWT Secrets
Broken Authentication
JOptimize detects this automatically
Scan your Java project in 30 seconds — free, no credit card.
// In com.example.OrderService.java line 42 public List<OrderItem> getOrdersByUser(String userId) { List<Order> orders = orderRepository.findAll(); // ❌ Loads entire table List<OrderItem> items = new ArrayList<>(); for (Order order : orders) { if (order.getUserId().equals(userId)) { items.addAll(order.getItems()); // ❌ N+1 lazy load } } return items; }
JOptimize Analysis Result:
{ "score": 32, "issues": [ { "severity": "CRITICAL", "rule": "Unbounded Query", "message": "findAll() without limit can load entire table (1M+ rows). Cost: OOM crash.", "line": 42, "suggestion": "Use pagination: repository.findByUserId(userId, PageRequest.of(0, 100))" }, { "severity": "CRITICAL", "rule": "N+1 Query Pattern", "message": "order.getItems() in loop = 1 query per order. Cost: 1000 orders = 1000 queries.", "line": 48, "suggestion": "Use JOIN FETCH: @Query(\"SELECT DISTINCT o FROM Order o LEFT JOIN FETCH o.items WHERE o.userId = ?1\")" } ] }
public List<OrderItem> getOrdersByUser(String userId, int pageNum) { Page<Order> orders = orderRepository.findByUserIdWithItems(userId, PageRequest.of(pageNum, 100)); return orders.flatMap(o -> o.getItems()).toList(); } // Repository @Query("SELECT DISTINCT o FROM Order o LEFT JOIN FETCH o.items WHERE o.userId = ?1") Page<Order> findByUserIdWithItems(String userId, Pageable pageable);
Result: Latency drops from 5000ms → 45ms (111x improvement). Memory usage stable.
joptimize scan ./src --categories MEMORY,DATABASE --fail-on CRITICAL
Exit code 1 if critical issues found → fails CI pipeline.
| Company | Code Size | Issues Found | Avg Latency Improvement | Memory Saved |
|---|---|---|---|---|
| FinTech SaaS | 500k LOC | 347 | 68% (2.1s → 670ms) | 40% |
| E-Commerce | 1.2M LOC | 891 | 42% (3.5s → 2.0s) | 28% |
| Healthcare API | 300k LOC | 156 | 55% (1.8s → 810ms) | 35% |
| Cloud Platform | 2.5M LOC | 1,204 | 71% (5.2s → 1.5s) | 52% |
Average impact: 59% latency reduction, 39% memory reduction, 7x fewer database queries.
Scenario: 10 developers, 1 production incident per quarter from missed performance issues
1 prevented incident = $76,000 saved = 6.8x ROI in first quarter alone.
Most customers prevent 2-3 incidents per year → 14-21x ROI.
| Plan | Team Size | Price | Features |
|---|---|---|---|
| Startup | Up to 5 devs | $299/mo | IDE plugins, basic analysis, GitHub integration |
| Pro | Up to 50 devs | $1,299/mo | All Startup + CLI, API access, 50+ rules, Slack alerts |
| Enterprise | Unlimited | Custom | All Pro + on-premise, custom rules, dedicated support |
No setup fees. Cancel anytime. 14-day free trial.
"JOptimize found N+1 queries we'd been chasing for months. Single fix dropped P99 latency by 2 seconds."
"Caught a hardcoded API key before it hit production. Saved us from a compliance audit."
"The memory leak detection is insanely accurate. We've prevented OOM crashes we didn't know existed."
No credit card required. Full feature access during trial.
JOptimize is the Java performance analyzer that catches issues before they hit production. 50+ anti-patterns detected, 59% avg latency improvement, 14x ROI from prevented incidents.
From memory leaks to N+1 queries to security vulnerabilities - JOptimize finds them all.
Start your free trial today. See how much performance is hiding in your code.
JOptimize finds N+1 queries, EAGER collections, and 70+ other issues in your Java codebase — in under 30 seconds.