Freelance › Projects › Administration › Database Performance Optimization & MySQL-to-PostgreSQL Migration
Database Performance Optimization & MySQL-to-PostgreSQL Migration
Employer
Andriy
Project parameters
Type of cooperationOne-time project
SectionAdministration
Prepaymentwithout prepayment
Payment methodsCash, Bank transfer
Acceptance of requestsfrom today, 14:24 until Aug 30, 2026
Project description
We run a web application whose traffic and data volume have grown steadily over the past two years, and the database has become the main bottleneck. Page loads that once felt instant now stall for several seconds during peak hours, background jobs pile up, and a handful of reporting queries occasionally lock tables long enough to time out user requests. We need an experienced database engineer to take ownership of a focused optimization effort: profile the workload, identify the queries and access patterns that are actually causing the pain, and turn that analysis into concrete, measurable improvements rather than guesswork.
The work has two connected halves. The first is optimization of the current system: capturing and analyzing slow-query logs, examining execution plans, and proposing indexing changes, query rewrites, and targeted schema adjustments (normalization where it helps, denormalization or summary tables where it helps more). We want each recommendation backed by before-and-after numbers on a realistic copy of our data. The second half is a planned migration between MySQL and PostgreSQL. This must be treated as a production-grade operation with zero data loss and minimal downtime, including data-type and collation mapping, converting stored logic and constraints, validating row counts and checksums on both sides, and a tested rollback path in case anything goes wrong.
You will work against a staging environment first and coordinate every production step with our team. We value clear communication, reproducible scripts over one-off manual fixes, and honest trade-off discussion. Please share relevant past experience with large datasets and any tooling you prefer for schema conversion and verification. Deliverables should be documented well enough that our own developers can maintain them afterward.
— Full slow-query audit with prioritized findings and reproduction steps
— Indexing plan, query rewrites, and schema change proposals with benchmark evidence
— Migration runbook covering data-type mapping, cutover sequence, and rollback
— Automated validation of row counts, checksums, and referential integrity post-migration
— Handover documentation and a short walkthrough for our engineering team
The work has two connected halves. The first is optimization of the current system: capturing and analyzing slow-query logs, examining execution plans, and proposing indexing changes, query rewrites, and targeted schema adjustments (normalization where it helps, denormalization or summary tables where it helps more). We want each recommendation backed by before-and-after numbers on a realistic copy of our data. The second half is a planned migration between MySQL and PostgreSQL. This must be treated as a production-grade operation with zero data loss and minimal downtime, including data-type and collation mapping, converting stored logic and constraints, validating row counts and checksums on both sides, and a tested rollback path in case anything goes wrong.
You will work against a staging environment first and coordinate every production step with our team. We value clear communication, reproducible scripts over one-off manual fixes, and honest trade-off discussion. Please share relevant past experience with large datasets and any tooling you prefer for schema conversion and verification. Deliverables should be documented well enough that our own developers can maintain them afterward.
— Full slow-query audit with prioritized findings and reproduction steps
— Indexing plan, query rewrites, and schema change proposals with benchmark evidence
— Migration runbook covering data-type mapping, cutover sequence, and rollback
— Automated validation of row counts, checksums, and referential integrity post-migration
— Handover documentation and a short walkthrough for our engineering team
