What is the difference between EXPLAIN and EXPLAIN ANALYZE?

EXPLAIN generates the query execution plan based on table statistics without running the query. EXPLAIN ANALYZE actually executes the query on the database to record real-world execution times, row counts, and buffer cache hits.

Is my query data or schema sent to any remote server?

No. All execution plan parsing, tree generation, and indexing algorithms run 100% locally in your browser memory.

How do I fix a Sequential Scan in PostgreSQL?

Sequential scans occur when the database must inspect every row in a table. Adding a B-Tree or composite index on the columns in your WHERE and JOIN clauses allows the engine to perform fast logarithmic Index Scans instead.

Developer

SQL Explain Plan & Performance Bottleneck Visualizer

Visualize database query execution trees, uncover high-cost sequential scans, inspect buffer I/O, and get actionable index creation advice.

Quick Answer & Summary

Paste PostgreSQL EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) or MySQL explain outputs to see a color-coded node tree highlighting slow operations, row estimation errors, and missing B-Tree indexes.

SQL Explain Plan & Performance Bottleneck Visualizer

Paste PostgreSQL or MySQL execution plans to visualize cost trees, identify sequential scan bottlenecks, and get index recommendations.

Execution Time

64.10 ms

Planning Time

1.20 ms

Peak Cost Score

3450

Bottlenecks

Raw EXPLAIN (FORMAT JSON)1063 chars

Run EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) SELECT ... in your database console and paste the output.

[
  {
    "Plan": {
      "Node Type": "Hash Join",
      "Total Cost": 3450.2,
      "Actual Total Time": 62.4,
      "Actual Rows": 12500,
      "Plan Rows": 12500,
      "Actual Loops": 1,
      "Shared Hit Blocks": 1200,
      "Shared Read Blocks": 45,
      "Plans": [
        {
          "Node Type": "Seq Scan",
          "Relation Name": "customer_orders",
          "Total Cost": 2850,
          "Actual Total Time": 48.2,
          "Actual Rows": 150000,
          "Plan Rows": 2000,
          "Actual Loops": 1,
          "Filter": "(order_status = 'pending')",
          "Shared Hit Blocks": 850,
          "Shared Read Blocks": 320
        },
        {
          "Node Type": "Index Scan",
          "Relation Name": "customers",
          "Index Name": "idx_customers_pkey",
          "Total Cost": 450,
          "Actual Total Time": 9.1,
          "Actual Rows": 12500,
          "Plan Rows": 12500,
          "Actual Loops": 1,
          "Shared Hit Blocks": 350
        }
      ]
    },
    "Planning Time": 1.2,
    "Execution Time": 64.1
  }
]

Query Optimization & Index Recommendations

Add B-Tree Index on customer_orders.order_status

Eliminate full table sequential scans by creating an index covering the filter predicate: (order_status = 'pending').

CREATE INDEX idx_customer_orders_order_status ON customer_orders (order_status);

Update Table Statistics (ANALYZE customer_orders)

The query planner's row estimate was off by a factor of 75.0x. Running ANALYZE updates table distribution histograms.

ANALYZE customer_orders;

Execution Plan Node HierarchyRoot Node

Hash Join

62.40 ms (97%)12,500 rows

Node accounts for 97.3% of total query runtime (62.40ms).

Seq Scanon customer_orders

48.20 ms (75%)150,000 rows

Sequential Table Scan on 'customer_orders' processed 150,000 rows without an index.

Filter: (order_status = 'pending')

Index Scanon customersusing (idx_customers_pkey)

9.10 ms (14%)12,500 rows

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Toolbox Editorial TeamVerified Authors

Systems & Security Engineers • Applied Cryptography & High-Performance Web Tools

Updated: August 2026

100% In-BrowserZero server storage

Standards AuditedRFC & ISO compliant

Peer ReviewedEditorial Policy

Documentation & Guide

How to Use SQL Explain Plan & Performance Bottleneck Visualizer

Run EXPLAIN in Database Console

Execute 'EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) SELECT ...' in pgAdmin, psql, or DBeaver.

Paste the JSON Plan Output

Paste the raw execution plan array into the visualizer.

Review Bottlenecks & Index Recommendations

Inspect red/amber highlighted nodes for slow sequential scans, high disk reads, and copy generated 'CREATE INDEX' snippets.

Practical Examples & Conversions

Input

Seq Scan on 'users' with Filter (active = true) processing 100,000 rows in 48ms

Output

Recommends 'CREATE INDEX idx_users_active ON users (active);' to convert into an index scan

Frequently Asked Questions (PAA)

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Authoritative Standards & Citations

Calculations and algorithms on this page are implemented and verified in strict accordance with the following official technical specifications:

IETF (Internet Engineering Task Force)

RFC 7519: JSON Web Token (JWT)

Standardized compact, URL-safe means of representing claims to be transferred between two parties.

W3C Recommendation

Web Cryptography API Specification

Standard JavaScript API for performing basic cryptographic operations in web applications.

IETF Standards Track

RFC 4122: A Universally Unique IDentifier (UUID) URN Namespace

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