Data Architecture That Powers Decisions
Database design, query optimization, and analytics solutions using PostgreSQL, MySQL, MongoDB, Redis, and Elasticsearch. Data infrastructure that performs at scale and delivers the insights your business needs.
What We Build
Data is the foundation of every software product. A poorly designed schema becomes a bottleneck that limits every feature built on top of it. Slow queries degrade user experience and drive customers away. Missing analytics mean decisions are made on gut feeling rather than evidence. Creatos DaaS provides database and analytics expertise that starts with getting the fundamentals right and extends to the reporting and data pipeline capabilities that turn raw data into business advantage.
Schema Design
Relational and document database schemas designed for your current features and future scalability. Proper indexing strategies, normalization decisions, and relationship modeling that prevent costly migrations later.
Query Optimization
Identifying and fixing slow queries that impact user experience. Typical results: 50-80% reduction in page load times for database-bound operations.
Reporting Dashboards
Business intelligence dashboards that give stakeholders real-time visibility into metrics that matter. Built with tools your team can maintain and extend.
ETL Pipelines
Automated data flows between systems. Extract data from source systems, transform it into usable formats, and load it into analytics platforms or data warehouses.
Database Migration
Moving between database platforms (e.g., MySQL to PostgreSQL), upgrading versions, or consolidating multiple databases with zero-downtime migration strategies.
Caching Strategy
Redis and Elasticsearch implementations that dramatically reduce database load and improve response times for frequently accessed data.
Technologies We Use
Working with a technology not listed here? Our expertise spans a wide range of frameworks, languages, and platforms. Discuss your stack →
Our Approach
Data Audit
Analyze current schema design, query patterns, indexing strategy, and performance bottlenecks. Identify quick wins and structural improvements.
Architecture Recommendations
Propose changes with clear rationale, expected performance improvements, and implementation priority.
Implementation
Execute changes with careful migration planning, rollback procedures, and zero-downtime strategies for production databases.
Performance Validation
Measure before-and-after performance with concrete metrics. Query times, page loads, and throughput improvements documented.
Documentation
Schema documentation, query optimization notes, and operational procedures for ongoing maintenance.
What You Get
- Optimized database schemas with migration files
- Query optimization reports with before/after performance metrics
- Reporting dashboards with documentation
- ETL pipeline configurations and monitoring
- Database migration scripts with rollback procedures
- Caching layer implementation and configuration
- Performance baseline documentation
Timeline Expectations
Database performance audit
3-5 days
Query optimization sprint
1-2 weeks
Schema redesign
2-4 weeks
Dashboard development
1-3 weeks
Full database migration
4-8 weeks
Ideal For
- Companies experiencing database performance degradation as their product scales
- Startups that need a scalable data architecture designed correctly from the start
- Teams building reporting and analytics capabilities for stakeholders
- Organizations migrating between database platforms or upgrading existing setups
- Agencies that need a database specialist for client projects with data-intensive requirements
Frequently Asked Questions
Ready to Fix Your Data Bottleneck?
Whether your database is crawling under load or you need an analytics platform built from the ground up, the discovery call is where we identify the right approach.