Dedicated to database excellence since 2014
Myth-isle was founded on a straightforward principle: databases should serve applications, not constrain them. Too often, we encountered organizations struggling with data structures that had grown organically without architectural oversight—tables with hundreds of columns, queries spanning dozens of joins, and indexes that existed without clear purpose.
Our founding team came from enterprise database administration backgrounds at major Canadian financial institutions. We understood the pressures of maintaining legacy systems while enabling new feature development. That experience shaped our consulting approach: pragmatic solutions that respect existing investments while creating paths toward modern, maintainable architectures.
Today, we work with organizations ranging from early-stage startups designing their first schemas to established enterprises migrating away from proprietary database platforms. Each engagement brings unique challenges, but our methodology remains consistent—understand the data, understand the access patterns, design accordingly.
A structured approach to database excellence.
Before writing a single line of DDL, we invest time understanding your business domain. What entities matter most? How do they relate? What questions will your application ask most frequently? These conversations with stakeholders—developers, product managers, data analysts—inform every subsequent decision.
We review existing systems where applicable, examining current schemas, common queries, and pain points. This baseline understanding ensures our recommendations address real problems rather than theoretical concerns.
Schema design happens iteratively. We present entity-relationship diagrams, discuss trade-offs between normalization levels, and prototype critical queries to validate performance assumptions. Nothing proceeds to implementation without stakeholder alignment.
For optimization engagements, we capture query execution plans from production workloads, identify the highest-impact opportunities, and propose changes in priority order. Each recommendation includes expected improvement metrics and implementation risk assessment.
We implement changes during agreed maintenance windows, with rollback procedures prepared for every modification. Post-implementation monitoring confirms expected outcomes.
Every engagement concludes with documentation and training. Your team receives schema diagrams, indexing rationale documents, and query optimization guides. We believe our job is to make ourselves unnecessary—to leave you with systems and knowledge that require no ongoing external support.
We implement appropriate normalization—typically third normal form—while recognizing that judicious denormalization sometimes serves performance goals. The key is making these decisions consciously rather than accidentally.
Indexes accelerate reads but slow writes. We analyze your read/write ratios, query patterns, and storage constraints to recommend indexes that provide maximum benefit with minimal overhead.
While we appreciate other database platforms, PostgreSQL's combination of reliability, features, and community support makes it our recommended choice for most use cases. Our deep expertise helps you leverage capabilities others overlook.
We explain our reasoning in plain language. Every recommendation comes with rationale that non-technical stakeholders can evaluate and question.
Perfect is the enemy of good. We deliver solutions that work within your constraints—budget, timeline, team capabilities—rather than insisting on theoretical ideals.
Our goal is your independence. We document thoroughly, train comprehensively, and remain available for questions long after formal engagements conclude.
Discuss your database challenges with consultants who understand both theory and implementation reality.
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