Database Engineering
Leverage the power of your databases, streamline your data-driven operations.
A high-performing database is the foundation of any successful data strategy. Database engineering ensures that foundation is solid, scalable, and secure. Nevertheless, building and maintaining a robust database demands specialized knowledge.
As a database engineering consulting firm, Dataiso designs and implements high-performance database solutions tailored to your specific needs. We ensure your data is secure, reliable, and readily accessible, providing the foundation for a robust and scalable data infrastructure.
Your challenges
Your challenges
Databases are the bedrock of any successful business application, providing secure storage and reliable access to critical information. And database management systems (DBMS) are the platforms that make this possible, ensuring data integrity, consistency, security, and accessibility.
However, today’s demanding applications require high performance and constant scalability. Meeting these needs can present significant challenges for IT operations and the business as a whole.
At Dataiso, we understand the complexities of designing and administering robust databases.
Performance bottlenecks
Sluggish databases can disrupt operations and lead to critical failures. As a result, many organizations regularly face financial losses and customer dissatisfaction.
Explosive data growth, out of control
Explosive data growth often leads to overload, storage limitations, and decreased system responsiveness. Many organizations face overwhelming performance issues and increased costs, hindering their operations.
Data integrity at risk
Rapidly evolving business needs lead many organizations to struggle to keep pace with change. Consequently, they grapple with outdated database structures, compromising their data integrity.
More vulnerable databases
Data loss can inflict severe economic damage, leading to reputational harm. Despite this, several organizations still lack robust backup and security policies, risking critical vulnerabilities.
Database migration pitfalls
High data volumes and application dependencies increase database migration complexity. Organizations often fail to overcome these challenges, resulting in long-lasting quality, security, and accessibility headaches.
Our key factors of success
Our key factors of success
Databases are the backbone of any data-driven organization, but mastering them depends on several key factors. Discover why Dataiso considers these factors essential for designing, implementing, and maintaining robust database solutions.
Selecting the optimal database technology is essential, as diverse DBMS options cater to various needs. From traditional SQL databases to modern NoSQL and NewSQL solutions, the right choice depends on specific requirements.
A robust backup plan and effective HADR strategy are crucial to minimize downtime and prevent significant financial losses in a disaster. Without these safeguards, an organization can face severe disruptions and damage to its reputation.
Providing robust database interoperability is crucial as it enhances data sharing across systems while improving collaboration. By ensuring seamless communication between databases, making informed decisions becomes easier.
Poor database performance can impact user experience and cripple business. Regular monitoring, resource optimization, and early issue detection ensure reliability and efficiency. This helps improve productivity and prevents costly downtime.
Like many database problems, the need for speed depends on the application being used. For example, speed is paramount when dealing directly with user queries, but perhaps much less so for long-running asynchronous scanning tasks. Thus, understanding and correctly setting the scaling properties of a database becomes a necessity.
A poorly designed data structure can compromise data integrity and erode trust, especially under data protection regulations. Effective data modeling is essential to mitigate risks related to referential integrity and consistency within a database.
Integrating database operations into DevOps streamlines deployments and improves efficiency. CI/CD (Continuous Integration/Continuous Delivery) practices help speed up the database management lifecycle through automated database provisioning.
Our approach
Our approach
Building high-performing databases requires a combination of technical expertise and a deep understanding of your business needs. At Dataiso, we collaborate with you to define optimal database designs (People), employ best-practice database development and maintenance methodologies (Process), and leverage cloud-based and on-premise database technologies (Technology).
Our approach ensures your database solutions are robust, scalable, and optimized for operational efficiency.
Our services
Our services
Dataiso provides cutting-edge database engineering services to help organizations achieve real-world results. We go beyond theoretical methods, delivering bespoke solutions that address your specific challenges and unlock new opportunities.
Database strategy and roadmap
- Maximize return on investment (ROI) by aligning database engineering objectives with the overall strategy.
- Drive growth by identifying high-impact opportunities where database engineering can make a significant difference.
- Develop a comprehensive database engineering roadmap for successful implementation strategies.
- Define the appropriate database technologies and tools to meet unique business needs and drive innovation goals.
- Strengthen database scaling strategies by implementing database operations (DBOps) principles.
- Demonstrate database value through compelling proofs of concept (PoCs) and proofs of value (PoVs).
Database audit and diagnosis
- Assess all existing database engineering practices, policies, and technologies.
- Identify gaps between the organization’s current state and database engineering best practices, including both technical and functional discrepancies.
- Assess database health and observability, including database models, queries, quality, consistency, and accessibility.
- Evaluate database management systems’ (DBMS) strengths and weaknesses (e.g., query plans, high availability, disaster recovery plans), using methods like performance testing and user feedback.
- Review database engineering and DBA ethics, sustainability, security, privacy, and compliance.
- Benchmark database engineering and DBA maturity against industry standards with proven maturity models.
- Maximize database engineering DBA investments through efficient optimization plans.
Database architecture deployment
- Implement tailored database architectures to meet requirements, such as tier-1, tier-2, and tier-N.
- Integrate best-in-class database management systems (DBMS) components, languages, and tools.
- Ensure scalability using smart sharding and partitioning.
- Enable data integrity and reliability through ACID (Atomicity, Consistency, Isolation, Durability) compliance by selecting the right RDBMS.
- Address normalisation and transaction management for efficient data accessibility.
- Ensure seamless RDBMS deployment on cloud platforms, on-premises infrastructure, or hybrid environments.
- Optimise RDBMS through smarter, proactive performance tuning techniques and efficient resource allocation.
- Enhance database design scalability by implementing object-oriented databases (OODBMS) using inheritance, encapsulation, polymorphism, and more.
- Unify object-oriented and relational models by developing object-relational databases (ORDBMS).
- Ensure seamless ODBMS deployment on cloud platforms, on-premises infrastructure, or hybrid environments.
- Optimize ODBMS through smarter, proactive performance tuning techniques and efficient resource allocation.
- Enable scalability and adaptability by selecting the right NoSQL model (e.g., document, key-value, column-family, graph, time series, search engine).
- Leverage integrated high-availability and fault-tolerance.
- Ensure seamless NoSQL deployment on cloud platforms, on-premises infrastructure, or hybrid environments.
- Optimize NoSQL databases through smarter, proactive performance tuning techniques and efficient resource allocation.
- Combine scalability with consistency by implementing NewSQL databases.
- Accelerate AI with vector databases (VDBMS).
- Handle hybrid workloads through HTAP (High Transactional/Analytical Processing) databases.
- Ensure seamless modern database deployment on cloud platforms, on-premises infrastructure, or hybrid environments.
- Optimize modern databases through smarter, proactive performance tuning techniques and efficient resource allocation.
- Strengthen database security and governance through proactive measures leveraging data protection and privacy best practices.
- Streamline and scale deployments with robust database operations (DBOps) practices.
Database model design
- Accurately translate complex business and technical requirements into well-defined, comprehensive database specifications.
- Identify relevant data entities, attributes, relationships, and constraints for efficient database model design.
- Design comprehensive conceptual (CDM), logical (LDM), and physical data models (PDM) using methods like Entity-Relationship (ER) modeling, UML (Unified Modeling Language), and ORM (Object-Relational Mapping) based on use cases.
- Ensure data consistency, integrity, and quality by leveraging strong data modeling standards and best practices.
- Take control of database model versioning and change management through effective version control systems.
- Enable ongoing database model refinement and validation with regular reviews and updates.
Query development
- Develop tailored queries, including stored procedures, functions, triggers, and ad-hoc queries, using SQL, JSON, GraphQL, and more.
- Tackle complex requirements through techniques like window functions and recursive common table expressions (CTEs).
- Improve indexing strategies and query execution plans for high-performance OLTP (Online Transaction Processing) workloads.
- Enable faster data retrieval through advanced optimization techniques like query caching, query hint, and query rewriting.
- Elevate query accuracy, completeness, integrity, and consistency with efficient query versioning and change management protocols.
- Enable ongoing query refinement and validation through regular reviews and updates.
High availability and disaster recovery (HADR) solution design
- Design robust HA configurations for critical database systems using methodologies like failover clustering, mirroring, logging, data replication, and beyond.
- Mitigate data loss and downtime with strong failover and failback mechanisms.
- Boost performance and consistency with optimized asynchronous and synchronous replication methods.
- Reduce downtime to near zero with tailored DRP mechanisms like snapshots, exports, and flexible backups.
- Establish proactive RTO (Recovery Time Objective) and RPO (Recovery Point Objective) parameters aligned with business requirements.
- Maintain HADR effectiveness with proactive disaster recovery drills, realistic simulations, and scenario-based tabletop exercises.
- Enable ongoing HADR refinement and validation through regular reviews and updates.
Backup and recovery
- Secure critical data with tailored backup plans aligned with protection requirements, including data retention policies.
- Prevent data loss through full, differential, and incremental backups.
- Enable granular exports for specific database objects like schemas, tables, and indexes.
- Reduce downtime with efficient data recovery processes like automated data restoration and granular data recovery.
- Ensure recovery plan effectiveness with regular testing and validation of backup and restoration scenarios.
- Enforce backup and recovery effectiveness with proactive disaster recovery drills, realistic simulations, and scenario-based tabletop exercises.
- Enable ongoing backup and recovery plan refinement and validation through regular reviews and updates.
Database performance optimization
- Pinpoint various database performance issues with precision for improved efficiency and responsiveness.
- Unlock the full potential of databases by addressing and eliminating bottlenecks and performance roadblocks.
- Streamline data retrieval with indexed queries and advanced caching mechanisms for lightning-fast results.
- Unlock substantial database performance gains with fine-tuned hardware and resources, including storage, I/O, memory, and CPU.
- Maintain database performance effectiveness with flexible capacity planning, robust performance baselines, and clear service-level agreements (SLAs).
- Enable ongoing database performance refinement and validation through regular reviews and updates.
Database migration
- Assess database migration requirements for cloud or on-premise deployments through detailed assessments like gap analysis, risk assessment, and more.
- Evaluate compatibility, scalability, and performance of existing database environments using efficient benchmarking and stress-testing methods.
- Build comprehensive database migration plans addressing technical, operational, and business specifications.
- Implement comprehensive cutover and rollback plans, leveraging robust testing and validation methods.
- Seamlessly migrate database assets to the target platform, with minimal disruption and risks.
- Leverage enhanced features and patches, by ensuring security and reliability with upgraded platform versions.
- Validate database integrity and quality post-migration for better accuracy, completeness, and consistency of business-critical information.
Database security and governance
- Safeguard database landscape with efficient security measures (e.g., data classification, access controls) based on industry standards like ISO 27001.
- Maintain transparency, accountability, and compliance with regulations like Data Act, GDPR, and CCPA through future-proof database governance.
- Strengthen database confidentiality, integrity, and availability using a comprehensive CIA triad model aligned with industry standards like 8000 and 25012.
- Uphold fairness, explainability, and privacy by addressing database engineering ethics and bias throughout the database management lifecycle.
- Enhance database monitoring and preventive methods through proactive data observability.
- Integrate database governance with overall data governance frameworks and best practices, including comprehensive policies and procedures.
Our benefits
Our benefits
- High-performance and scalable databases.
- Secure and protected database environments.
- Strengthened database administration (DBA) best practices for easy maintenance.
While working with databases may seem straightforward in theory, the increasing complexity of evolving needs presents various challenges. This underscores the need for robust database management practices to support business and operational efficiency.
At Dataiso, we empower organizations to harness the full potential of their databases, driving greater outcomes. Collaborate with us to explore how we can help you.