Relational databases
Transactional systems for structured data and strong consistency.
- PostgreSQL
- MySQL

Baaz designs and manages data layers for transactional and analytical systems using relational and NoSQL databases with performance-first modeling.
We build database strategies that support growth, high availability, and operational clarity from day one.
Databases, search engines, and data practices we use for strong performance, safe migrations, and operational clarity as your workloads grow.
Transactional systems for structured data and strong consistency.
Schema-flexible and real-time data layers for modern applications.
Low-latency access and full-text or analytics-style indexing.
Modeling, migration, and resilience work that keeps data trustworthy.
We evaluate current schemas, workloads, and growth forecasts to define an optimization roadmap.
We improve data modeling, indexing, and query patterns for better reliability and throughput.
We execute migration and modernization plans with staged rollout and validation safeguards.
We continuously monitor health metrics and tune performance to keep databases stable at scale.
Schema, indexing, and migration work with clear ownership—we optimize for your workloads today and the scale you are heading toward.
Query plans, indexing, and caching strategies driven by evidence—not guesswork or one-size-fits-all defaults.
Staged cutovers, validation checkpoints, and recovery paths so data moves without surprise downtime.
Relational, document, cache, and search layers chosen for your access patterns—not buzzwords.
Design relational and NoSQL architectures aligned to product requirements and future scale.
Move legacy data systems to modern stacks with low risk and minimal downtime.
Optimize queries, indexes, and storage strategy to improve speed and efficiency.
Implement resilient data protection and recovery workflows for business continuity.
We work with PostgreSQL, MySQL, MongoDB, Firebase Firestore, Redis, and Elasticsearch. Database selection depends on your data model, consistency requirements, query patterns, and scalability targets.
Relational databases like PostgreSQL are best for structured data with complex relationships and strict consistency needs. NoSQL options like MongoDB are better for flexible schemas, high write throughput, or document-style data. We assess your use case and recommend the appropriate fit.
Yes. We plan migrations with staged rollouts, shadow writes, validation checkpoints, and rollback safeguards to minimize operational risk. Zero-downtime migrations are achievable for most production environments with proper preparation.
We start with query analysis and execution plan review, then address index coverage, schema normalization, and caching strategies. For persistent bottlenecks we consider read replicas, connection pooling, or partitioning depending on your workload profile.
We configure automated backups, point-in-time recovery, off-site replication, and documented restore procedures. Recovery time objectives and recovery point objectives are defined during the architecture phase to match your business continuity requirements.

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