Providing services to improve corporate database operation efficiency

Founded in 2005, Openmade Consulting is recognized for its expertise in database modeling and SQL performance tuning. It develops its own performance failure prevention solution, "OpenPOP," and open source database migration automation technology. It also provides a variety of services to improve database resource and operational efficiency.

This company has taken a leap forward by developing an AI-based DB auto-tuning solution, combining its accumulated SQL tuning data and consulting expertise with artificial intelligence (AI). The recently launched "Query-Medic" combines the inference capabilities of a large-scale language model (LLM) with over 20 years of SQL tuning experience. It automatically detects SQL that degrades performance and excessively consumes DB resources without human intervention, automating the entire process from tuning to verification of the results. It is the culmination of Openmade Consulting's AX strategy.

Automating the entire SQL tuning process with AI LLM

The core of Openmade Consulting's AX strategy can be defined as 'automating the entire SQL tuning process with AI to prevent DB performance degradation in advance and secure DB resource efficiency.'

Key features include: First, end-to-end SQL auto-tuning across the entire development, testing, validation, and operation cycle automatically detects SQL that consistently degrades performance and consumes excessive resources, and consistently performs automatic tuning and results validation.

Second, it automatically verifies the performance improvement effect and the consistency of the resulting data before and after tuning, providing only verified SQL to the requester or performance manager. Third, it analyzes the index impact to proactively identify any performance changes to all relevant SQL using the index and support the decision on whether to apply the index.

Fourth, we provide quantitative analysis of the DB load and usage reductions resulting from the implementation of the QueryMedic solution. Furthermore, operational stability was ensured through implementation and verification in multiple customer environments prior to launch. Finally, QueryMedic can be used from development to production databases with a simple registration process, and it supports various options required for SQL tuning management. Openmade Consulting is currently working on a feature update for QueryMedic, which is currently primarily available for Oracle databases, to also support TmaxTivero databases.

sLLM advancement and SaaS conversion

Openmade Consulting plans to expand its business into an AI-based DB performance management platform based on QueryMedic. By 2026, it plans to develop sLLM, a specialized SQL tuning platform, through advanced learning utilizing large-scale tuning case datasets and tuning expertise. This model will incorporate optimization algorithms tailored to the characteristics of each DBMS, significantly improving accuracy and processing speed compared to existing general-purpose LLMs. According to CEO Choi Young-cheol, sLLM development is expected to be completed by the first half of 2026, and the company plans to continuously focus on performance enhancements through proof-of-concept (PoC).

Furthermore, starting in 2026, the company aims to expand the scope of tuning automation to open-source databases and transition to a cloud-based SaaS service to enter overseas markets. Preliminary work has begun to provide the on-premises QueryMedic solution as a SaaS offering on leading cloud service providers like Amazon Web Services (AWS) and Microsoft (MS), and basic discussions have been completed. By expanding QueryMedic to a SaaS format, Openmade Consulting aims to develop it into an AI SQL optimizer platform that global companies can easily integrate into their own database environments.

Openmade Consulting CEO Choi Young-cheol said, “QueryMedic is an AI solution that goes beyond simple SQL tuning and aims to maximize the effect of reducing operating costs (DB resources, cloud) through innovation in DB resource efficiency.” He added, “Through collaboration between DB performance managers and AI, we will open an era of complete automation of DB/App performance optimization.”

[Interview] "We're ushering in an era of smart tuning, where AI can automatically tune SQL."

Q. Please introduce the AI capabilities that Open Made Consulting possesses.

Openmade Consulting is driving intelligent database operations by combining over 20 years of accumulated SQL performance tuning data and database diagnostic expertise with AI. In particular, its proprietary QueryMedic utilizes a large-scale language model (LLM)-based inference architecture to automate the entire tuning process, from SQL detection and tuning to verification and impact analysis.

AI analyzes system logs and execution plans to automatically identify resource-intensive SQL queries and learn execution patterns to suggest optimal query structures. This level of AI capability, capable of assisting or even replacing the role of a database administrator, is a key AI capability and strength of Openmade Consulting.

Q. What AI strategy does Openmade Consulting focus on?

The key is to publicly promote the idea of "automating the entire SQL tuning process with AI" and expand it to companies across various industries. The essence of database performance management lies in SQL efficiency, and until now, bottlenecks have been identified manually by skilled experts. To overcome this limitation, we are converting the SQL tuning ruleset and performance data accumulated over 20 years into an AI-powered inference structure, automating the entire database operation process.

To achieve this, the integration of LLM and the company's SQL knowledge base is crucial. The AI is designed to analyze SQL execution plans and logs to identify the causes of performance degradation, suggesting and automatically rewriting optimal query structures. Specifically, a self-learning loop is applied, allowing the AI to continuously learn from tuning results, accumulating tuning patterns optimized for specific DBMS environments over time. This structure aims for "autonomous DB operation where AI independently improves performance," rather than simple automation.

Openmade Consulting is using this technology to evolve AI toward domain specialization (verticalization). Instead of a general-purpose LLM, the company is developing a specialized LLM (sLLM, specialized LLM) specifically for SQL tuning. Through this, it plans to internalize optimization algorithms tailored to the specific characteristics of each DBMS.

Additionally, QueryMedic will be offered as SaaS by 2027, and will be developed into an AI SQL optimizer platform that global companies can easily apply to their own DB environments.

Q. Please give a detailed introduction to the recently released QueryMedic.

QueryMedic is an AI-based SQL auto-tuning solution officially launched by Openmade Consulting on October 20th. It automatically detects, tunes, and verifies performance-degrading SQL queries 24/7, without human intervention. LLM analyzes SQL execution plans and logs to identify bottlenecks and automatically generates and verifies optimized queries based on execution patterns. In particular, its index tuning impact analysis feature allows users to predict how specific index changes will affect the performance of other SQL queries, dramatically improving database operational stability.

Its effectiveness in operational environments has also been proven. QueryMedic operates 24/7, 365 days a year, monitoring both the verification and operational databases simultaneously to proactively prevent major issues such as slow application response times, excessive resource usage, and increased cloud costs. Companies that have actually applied QueryMedic have seen a reduction in repetitive DB resource expansion and reliance on external tuning, as well as reduced SQL management costs and performance stabilization.

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Source: IT Daily ( http://www.itdaily.kr/news/articleView.html?idxno=236076 )

Reporter Park Jae-hyun pajh0615z@itdaily.kr