Apps Slowing Down Under Load
Identify N+1 patterns, missing indexes, and locking issues and fix them so user-facing latency drops without rewriting the app.
Who we build for
Who We Build Database Performance For
Slow queries are usually a design problem, not a hardware one. We audit, redesign, and optimise data layers relational and NoSQL so your application stops paying the cost of unindexed reads and unscalable schemas.
Data-Intensive Products
Schema design, indexing strategy, and caching layers tuned for analytics workloads, multi-tenant data, and growing record counts.
Teams Migrating Databases
Plan and execute schema changes, engine migrations (e.g., MySQL → PostgreSQL), and shardings with reversible cutovers and zero-downtime targets.
Search-Heavy Applications
Add Elasticsearch or OpenSearch alongside your primary store for fast retrieval, autocomplete, and analytics without overloading your DB.
Why Chayaniq for databases
Database Design & Performance Benefits
Database performance is usually a design problem, not a hardware one. Here is what we bring to make your data layer fast, reliable, and ready for the next 10× of load.
Database Architecture Design
Relational and NoSQL schemas modelled around how your application actually queries instead of forcing data into a single shape.
Query Optimisation & Indexing Strategy
Identify and fix N+1 patterns, missing indexes, and locking issues so user-facing latency drops without rewriting the app.
MySQL, MongoDB & Redis Performance Tuning
Engine-specific configuration, connection pooling, and slow-query analysis tuned to your actual workload, not a generic guide.
Elasticsearch / OpenSearch Integration
Search and analytics workloads moved off your primary DB for fast retrieval, autocomplete, and aggregations at scale.
Caching Layer Implementation (Redis)
Cache patterns chosen for your read/write mix read-through, write-behind, or rate-limit caching without invalidation bugs.
Database Migration & Schema Evolution
Reversible migrations and zero-downtime schema changes so big-bang cutovers stop being the only option for evolving your data model.
Industries we serve
Database Performance Across Industries
Healthcare records, e-commerce catalogs, financial transactions, and IoT telemetry all stress data layers differently. We tune databases for each vertical's real workload.
Remote patient monitoring
- Real-time collection of wearables data
- Enhanced doctor-patient communication
- Comprehensive view of patient health data
- Data-driven report generation
- Seamless integration with existing systems
- Improved patient outcomes
Electronic medical records (EMR)
- Interoperability of medical data across departments
- HIPAA / GDPR compliant solutions
- Improved patient care
- Quick access to patient records, vitals, and lab results
- Enhanced security and privacy of patient health data
Document management
- Compliant documentation workflow
- Streamlined management of health information
- Integrations with existing systems for a 360° data view
- Secure file sharing and access management
Insurance verification
- Automated medical insurance eligibility
- Proactive identification of coverage issues
- API-ready and HIPAA-compliant
How we work
Our Process for Database Optimisation
Database engagements work best when they start with measurement. Our process is audit-first, fix-second so every change has a measurable impact you can defend.
Audit & Profiling
We profile your slow queries, index usage, and locking patterns building a clear picture of where time is actually being spent.
Architecture Review
We review schemas, access patterns, and growth projections and recommend changes ranked by impact-to-effort.
Tuning & Refactor
Index changes, query rewrites, and connection-pool tuning applied with measurable before/after numbers, not vibes.
Caching & Search
Redis caching layers and Elasticsearch integration where they pay off moving load off the primary store cleanly.
Migration
Zero-downtime schema changes and engine migrations using parallel-run, dual-write, or strangler patterns chosen for fit.
Monitoring
Slow-query dashboards, cache-hit metrics, and capacity alerts so regressions surface early instead of as customer complaints.
How we ship database performance
Database performance is usually a design problem, not a hardware one. We engage as auditors, architects, or hands-on optimisers depending on what your data layer needs.
Relational and NoSQL schemas modelled around how your application actually queries instead of forcing data into a single shape.
- Normalisation, denormalisation, and access-pattern-driven design
- Hybrid relational + document approaches when it fits
- Multi-tenant data partitioning when growth demands it
Our stack
Our Database Technology Stack
Relational, document, search, and cache layers picked for fit, not fashion, and tuned to the actual workload your application has.
Relational Databases
- MySQL
- PostgreSQL
- Amazon Aurora
- RDS
NoSQL & Document
- MongoDB
- DynamoDB
- Cassandra
Caching
- Redis
- Memcached
- DAX (DynamoDB cache)
Search & Analytics
- Elasticsearch
- OpenSearch
- ClickHouse
Migration & Tooling
- Liquibase / Flyway
- pt-online-schema-change
- Prisma / Drizzle ORM
CDC & Streaming
- Debezium
- Kafka Connect
- AWS DMS
Perspectives
Ideas that pair with Database Design, Optimization & Performance
Short reads from how we ship architecture, product, and ops. Same themes as this service, different angles.
March 2026
Why Your API Is Slow (And How to Fix It Without Rewriting Everything)
N+1 queries, missing indexes, no caching the most common API latency culprits and the practical fixes you can apply today.
Continue readingFebruary 2026
MongoDB vs MySQL: How to Actually Choose
The real question is data shape not hype. A practical breakdown for developers building real systems, including hybrid approaches.
Continue readingJanuary 2026
Redis Beyond Caching: 5 Use Cases That Will Change How You Think About It
Rate limiting, pub/sub, sessions, leaderboards, and distributed locks Redis does far more than caching.
Continue reading
