Rival Arya Pirmansah
Backend Engineer — Data & Query Performance
40min → 1min import · 108× faster response times · APIs that scale
108×
Fastest query speedup
97%
Import time reduced
20s
1M records inserted (was 3 min)
Performance case studies
View allWhy Your Database Is Slow (It's Not the Hardware)
Pages that used to take 3 seconds to load now respond almost instantly.
108× faster on list queries, up to 666× faster on single-record lookups, no hardware changes.
8.8M rows
Dataset
666×
Best speedup
99.85%
Latency reduction
Inserting 1 Million Records into MongoDB — What Actually Makes It Fast
A batch job that used to run over 3 minutes, or crash outright, now finishes in 20 seconds.
1M records processed in 20s using batched inserts and concurrency, down from 3m19s or an out-of-memory crash.
1M rows
Dataset
20s
Best time
3m 19s
Worst (completed)
Reducing Excel Import from 40 Minutes to 1 Minute
An import that blocked the operations team for 40 minutes, with no feedback on success or failure, now finishes in about a minute.
97% faster (40 min → ~1 min) after fixing N+1 queries and switching to bulk inserts.
40 min
Before
~1 min
After
97% faster
Improvement
Building a Public Face Recognition API — And Why I Over-Engineered It
A face-lookup feature shipped as a working API in under a second per request, without the scale infrastructure it didn't need yet.
3 endpoints, ~737ms–1.8s latency across 20K+ facial records on CPU-only inference.
20K+
Facial records
737 ms
Fastest endpoint
FaceNet512
Model
Core Projects
View all
LiveRivalistic - Face Recognition API
Production-ready face recognition API processing 20,000+ facial records with sub-2-second inference latency. Built to simplify facial verification integration for developers with three core endpoints achieving sub-1-second response times.
CompletedHandling 1 Million Records
Implemented optimized bulk insert strategies reducing insert time from ~3 minutes to ~20 seconds. Performance tuning achieved through efficient data handling and database optimization.
LiveIMDB Performance Optimization
Optimized backend application achieving 108.22× faster response times (2876.061ms -> 26.576ms) with ~99% latency reduction. Focused on code and database design improvements.
LiveTokoFiktif
RAG-powered customer service chatbot for a fictional Indonesian e-commerce company. Built on benchmark findings showing an 8B model with RAG matches 70B accuracy at 88% lower cost and 41% lower latency.