EverSQL - AI-powered SQL query optimization for PostgreSQL and MySQL

What is EverSQL

Database query performance degradation represents one of the most persistent challenges facing software teams today. Slow queries directly impact user experience, conversion rates, and overall business performance. Traditional SQL optimization requires specialized DBA expertise, extensive manual analysis, and significant time investment—resources that many organizations simply do not have.

EverSQL is an AI-driven automated SQL query optimization platform designed to address these challenges without requiring code changes or deep database expertise. The platform leverages advanced machine learning algorithms to automatically analyze and rewrite SQL queries for PostgreSQL and MySQL databases, generating optimal execution plans that dramatically improve performance. This 100% non-invasive approach means teams can achieve substantial performance gains without modifying any application code or database configuration.

The core value proposition centers on the platform's ability to deliver measurable results with minimal effort. Organizations using EverSQL report average query speed improvements of 25x, with some optimizations achieving even higher gains. This translates directly to faster application response times, improved user satisfaction, and reduced infrastructure costs. The platform has been adopted by over 100,000 software engineers across 90 countries, including major enterprises such as Nike, Salesforce, Amazon, Bank of America, and PostgreSQL.

Founded in 2019 by Oded Valin and Tomer Shay, EverSQL focused exclusively on database optimization from its inception. In November 2023, the company was acquired by Aiven, a leading open-source cloud data platform provider. This acquisition integrated EverSQL into Aiven's comprehensive cloud database ecosystem, enabling the company to offer the optimization tool completely free of charge. Teams can now access EverSQL's capabilities directly through Aiven's platform, combining query optimization with managed database services for a complete data infrastructure solution.

Core Capabilities of EverSQL

The EverSQL platform provides five primary capabilities that address different aspects of database performance optimization. Each capability is designed to deliver measurable business value while minimizing the technical complexity typically associated with database tuning.

Automated SQL Query Optimization forms the foundation of the platform's offering. The AI engine analyzes incoming SQL queries and automatically generates rewritten versions that execute more efficiently. This goes beyond simple query restructuring—the system employs deep learning models to understand query patterns and generate optimal execution plans tailored to each specific database environment. Users simply submit their SQL queries and receive optimized versions along with detailed explanations of the improvements. This capability alone has driven the 25x average performance gains reported by customers.

Continuous AI Performance Monitoring provides ongoing visibility into database health through non-invasive sensors. These agents run in the background, continuously采集 performance metrics without accessing any sensitive customer data. The system analyzes these metrics in real-time, identifying performance degradation before it impacts end users. When issues are detected, actionable optimization recommendations are generated within minutes, allowing teams to address problems proactively rather than reactively.

Cost Optimization Recommendations helps organizations control their cloud database spending. The AI analyzes resource utilization patterns and identifies opportunities to reduce infrastructure costs—primarily through deletion of redundant indexes and architecture optimization. These recommendations directly translate to lower CPU usage, reduced memory consumption, and decreased storage costs, resulting in measurable reductions in monthly database bills.

Database Observability delivers comprehensive performance visualization through integrated monitoring dashboards. The platform supports seamless integration with industry-standard tools including Prometheus and Grafana, enabling teams to incorporate database performance data into their existing monitoring workflows. This is particularly valuable for organizations managing multiple database instances across different environments.

Free Online Tools extend the platform's value further. Users can access a collection of complimentary utilities including an SQL syntax checker, SQL optimizer, PostgreSQL Playground, SQL formatter, and Kafka visualization tools. These tools are available directly through Aiven's website without requiring registration.

Who Uses EverSQL

EverSQL serves a diverse range of organizations and use cases, though four primary scenarios represent the most common adoption patterns. Understanding these scenarios helps potential users identify whether the platform aligns with their specific needs.

Scenario One: Slow Queries Impacting Business Response Times represents the most frequent use case. Organizations experiencing sluggish application performance due to inefficient database queries submit their SQL to EverSQL and receive AI-optimized versions along with index recommendations. The results speak for themselves—customers report query speed improvements of up to 25x, transforming previously慢 queries into near-instantaneous responses. This directly improves user experience, reduces bounce rates, and supports better business metrics.

Scenario Two: Uncontrolled Database Costs affects many organizations operating in cloud environments. As databases grow and query volumes increase, monthly bills can spiral beyond budget expectations. EverSQL's cost optimization engine identifies redundant indexes that consume storage and slow down write operations, then recommends their removal. Combined with architecture optimization suggestions, these changes reduce CPU usage, memory consumption, and storage requirements—directly lowering monthly infrastructure expenses.

Scenario Three: Limited DBA Resources describes a common challenge for mid-sized companies and startups. Many organizations lack dedicated database administrators, leaving development teams to handle performance issues without specialized expertise. EverSQL democratizes database optimization by automating what traditionally required years of experience. Teams no longer need to understand complex execution plans or indexing strategies—the AI generates clear, actionable recommendations with step-by-step implementation guides. Customers report saving approximately 140 hours per week on database optimization tasks.

Scenario Four: Difficult Performance Problem Diagnosis plagues operations teams across industries. When production performance degrades, identifying the root cause among countless potential factors can take days. EverSQL's continuous monitoring sensors capture comprehensive performance data, automatically generating diagnostic reports that pinpoint bottlenecks and provide specific remediation guidance. This transforms what was once a frustrating debugging exercise into a structured, solvable problem.

Technical Characteristics

The EverSQL platform architecture reflects careful engineering decisions balancing performance, security, and ease of deployment. Understanding these technical foundations helps organizations evaluate the platform's suitability for their specific requirements.

AI Query Rewriting Engine represents the platform's core technology innovation. The system employs deep learning models trained on millions of real-world SQL queries to understand patterns and optimization opportunities. When analyzing a submitted query, the engine considers multiple factors including table statistics, index availability, join orderings, and execution plan alternatives. The output is a rewritten query that produces identical results but through more efficient execution paths. This automated approach eliminates the guesswork traditionally associated with manual query tuning.

Intelligent Index Recommendation complements the query rewriting capability by addressing underlying data structure issues. The AI analyzes actual query workloads to determine which indexes would provide the greatest performance benefits. Importantly, the system also identifies redundant or unused indexes that consume storage and slow down write operations. This bidirectional optimization ensures organizations maintain only the indexes that genuinely improve performance.

Non-Invasive Monitoring Architecture enables continuous performance oversight without compromising security. The optional sensor component runs as a lightweight agent that collects performance metrics—query response times, resource utilization, wait events, and similar indicators. Critically, this sensor never accesses actual data content, including query parameters, table data, or any personally identifiable information. Organizations maintain complete data sovereignty while benefiting from comprehensive performance insights.

Multi-Database Support currently encompasses PostgreSQL and MySQL, the two most widely deployed open-source relational databases. This focused approach allows the development team to optimize their AI models specifically for these platforms rather than spreading resources across numerous database engines. Both community and commercial database variants are supported.

Security and Compliance meet enterprise-grade requirements through multiple layers of protection. All data transmission uses encryption, and stored metrics are encrypted at rest. The platform has achieved compliance with major regulatory frameworks including ISO/IEC 27001:2022, ISO/IEC 27017:2021, ISO/IEC 27018:2020, ISO/IEC 27701:2019, ISAE 3000 Type 2 / SOC2 Type II, GDPR, CCPA, HIPAA, and PCI-DSS. These certifications are maintained through Aiven's unified compliance program following the 2023 acquisition.

Ecosystem and Integration

EverSQL's integration into the Aiven platform represents a significant evolution in the product's trajectory, providing users with access to a broader ecosystem of cloud data services while maintaining the optimization capabilities that made the original product valuable.

Aiven Platform Integration occurred in November 2023 when Aiven acquired EverSQL to enhance its cloud data platform's AI optimization capabilities. Aiven, founded in 2016, has established itself as a leading provider of open-source cloud data infrastructure, offering managed services for databases, message queues, and analytics tools. The acquisition positioned EverSQL as a core component of Aiven's optimization strategy, available completely free to all platform users. This integration provides a seamless experience for existing Aiven customers, who can enable EverSQL optimization directly from their console without additional setup.

Monitoring Tool Integration ensures EverSQL fits naturally into organizations' existing operational workflows. The platform exposes performance metrics in formats compatible with Prometheus, the industry-standard metrics collection system. These metrics can be visualized through Grafana dashboards or other compatible visualization tools. This approach respects organizations' investments in their monitoring infrastructure while adding database-specific optimization insights.

Free Access Availability removes previous barriers to adoption. Organizations can begin using EverSQL immediately by visiting the Aiven SQL Query Optimizer page. No credit card or commitment is required to get started. This free tier provides meaningful value for individual developers and small teams, while larger organizations can leverage the optimization capabilities alongside Aiven's full managed database offerings.

Complete Data Platform emerges from the combination of EverSQL optimization and Aiven's managed database services. Organizations can provision optimized PostgreSQL or MySQL databases through Aiven, apply EverSQL's AI optimizations, implement continuous monitoring, and manage costs—all through a unified platform. This end-to-end approach simplifies vendor management and ensures compatibility between optimization recommendations and underlying database configurations.

Frequently Asked Questions