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PawSQL is an advanced, automated SQL performance optimization platform designed to assist developers, database administrators, and data engineers in identifying and resolving database query inefficiencies. Supporting a wide array of relational database management systems—including MySQL, PostgreSQL, Oracle, MariaDB, and openGauss—the platform provides comprehensive SQL tuning capabilities. These encompass intelligent query rewriting, automated cost-based index recommendations, and deep execution plan analysis. By integrating directly into developer workflows via its IntelliJ IDEA plugin or its cloud-based advisory interface, PawSQL reduces the friction of manual database tuning. Its proprietary optimization engine evaluates poorly performing queries, suggesting syntactical optimizations and necessary indexing strategies to minimize latency. This proactive approach significantly decreases database CPU and memory consumption while improving overall application response times. PawSQL serves as a robust performance guardrail in modern CI/CD pipelines, systematically catching sub-optimal SQL before it reaches and degrades production environments.
PawSQL is an advanced, automated SQL performance optimization platform designed to assist developers, database administrators, and data engineers in identifying and resolving database query inefficiencies.
Explore all tools that specialize in automated syntactical optimization. This domain focus ensures PawSQL delivers optimized results for this specific requirement.
Explore all tools that specialize in automated cost-based index suggestions. This domain focus ensures PawSQL delivers optimized results for this specific requirement.
Explore all tools that specialize in intellij idea plugin integration. This domain focus ensures PawSQL delivers optimized results for this specific requirement.
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Evaluates the structural schema, cardinality, and query predicates to generate highly optimized DDL for single-column and composite indexing.
Applies a library of over 60 semantic rewrite rules to refactor complex, inefficient SQL statements into optimized equivalents.
Natively parses MyBatis XML files to extract, resolve, and tune dynamic SQL blocks (e.g., <if>, <foreach>).
Parses raw EXPLAIN and EXPLAIN ANALYZE outputs, rendering them into a standardized, visual node graph.
Seamlessly processes and formats SQL syntax across MySQL, PostgreSQL, Oracle, MariaDB, and openGauss.
Integrates directly with automated build and deployment pipelines to scan committed code for SQL performance regressions.
Register an account on PawSQL Cloud or install the PawSQL IDE plugin.
Configure the target database dialect and connection, or manually input the database schema (DDL).
Input the problematic or target SQL query into the advisor.
Execute the tuning engine to generate optimization recommendations and index DDL.
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