DB Comparison Tool: 12 Best Database Comparers for 2026

Choosing the right db comparison tool is one of those decisions that looks small on a sprint board but compounds fast: pick the wrong one and your team spends hours reconciling schema drift, chasing phantom data mismatches, or running risky manual migrations against production. Pick the right one and database diff becomes a routine five-minute step between every environment promotion. This guide cuts through the noise with honest, side-by-side coverage of 12 serious database compare software options — paid and free, GUI and CLI, cloud-native and on-premise — so you can match a tool to your exact workflow instead of defaulting to whatever the first Google result advertises.

The landscape has changed noticeably since 2024. Open-source contenders like DBDiff and DataFold's data-diff have matured, Liquibase's free tier now covers most CI/CD use cases, and browser-based tools have carved a niche for quick SQL dump review. Whether you work on SQL Server, MySQL, PostgreSQL, Oracle, or a document store like MongoDB, there is a database comparer designed for your stack. If you are specifically evaluating MySQL tooling, see our deep-dive on the best MySQL database compare tools; for pure query and script diffing, the SQL compare guide covers that narrower use case in full.

Before we rank tools, the next two sections define exactly what db compare means and why the schema/data split matters more than any feature checkbox. If you already know the theory, jump straight to the 12-tool comparison table.

What Is a DB Comparison Tool?

A db comparison tool — also called a database comparer or database compare utility — is software that reads two database states (live connections, snapshots, or exported scripts), identifies every structural or content difference between them, and typically generates a synchronization script to resolve those differences. At its core, the problem is the same as text diff: given source A and target B, produce a minimal change set that transforms A into B.

The challenge is that relational databases are not flat text files. Tables have dependencies; foreign keys impose ordering constraints on synchronization; data types interact with collations and character sets; indexes exist to serve queries, not structure. A naive line-by-line diff of two mysqldump outputs produces so many false positives (column order, comment variations, AUTO_INCREMENT counters) that it is nearly useless. Dedicated data comparison tools parse the schema semantically, normalize representations, and produce a dependency-aware change script that will not break referential integrity.

Core use cases

• Pre-deployment audit — verify a migration script actually produced the expected structure in staging before promoting to production.
• Environment drift detection — catch ad-hoc schema changes applied directly to production that were never captured in a migration file.
• Data validation — confirm that an ETL job, replication stream, or data migration moved every row correctly.
• Regulatory compliance — demonstrate that production and DR databases match, or document the exact state of a database at audit time.
• CI/CD pipeline gate — block a deployment if the database diff between the migration plan and the current live schema contains unexpected changes.

The analogy to file-level diff is intentional. Just as developers use the diff command in Unix to compare text files or review changes in a Linux terminal, DBAs use a database diff tool to compare schemas and datasets. The underlying algorithm is more complex, but the workflow — inspect, review, apply — is identical.

Schema vs. Data: Two Modes Every Database Comparer Needs

Every serious database comparer must support both schema comparison and data comparison because they solve fundamentally different problems, use different algorithms, and generate different output. Conflating the two leads to picking a tool that handles one well but silently skips the other.

Schema comparison

Schema comparison reads the structural definition of a database: tables, columns, data types, nullable constraints, default values, indexes, unique constraints, foreign keys, check constraints, stored procedures, functions, views, and triggers. It does not read a single data row. The output is a set of DDL statements — ALTER TABLE, CREATE INDEX, DROP VIEW — that transform the source schema into the target schema. Use it before every deployment to ensure your environment is in the expected baseline state.

Data comparison

Data comparison reads the actual rows stored in tables and identifies additions, deletions, and modifications at the row level. This is computationally heavier: a table with 50 million rows requires efficient chunking and checksum strategies to avoid reading every byte. The output is DML — INSERT, UPDATE, DELETE — that reconciles content between two environments. Use it to validate ETL pipelines, check replication consistency, or confirm a data migration landed correctly.

Why both matter

Schema drift is the most common cause of deployment failures. Data drift is the most common cause of silent data integrity bugs. A db compare workflow that checks only schema misses half the picture. Most commercial tools — dbForge, Redgate, EMS, ApexSQL — ship separate "Schema Compare" and "Data Compare" modules. Open-source tools tend to focus on one mode; choose accordingly.

The 12 Best Database Comparison Tools for 2026

The table below covers all 12 tools on the key axes a DBA or developer needs to make a decision: supported databases, comparison modes, deployment model, and pricing tier. Detailed per-category breakdowns follow in later sections.

Tool	Databases	Schema	Data	Deployment	Pricing
dbForge Schema/Data Compare	SQL Server, MySQL, Oracle, PostgreSQL	Yes	Yes	Windows GUI	Paid (free trial)
Redgate SQL Compare	SQL Server	Yes	Yes (SQL Data Compare)	Windows GUI + CLI	Paid (~$595/yr)
Microsoft SSDT / SqlPackage	SQL Server, Azure SQL	Yes	No	Cross-platform CLI	Free
Altova DiffDog	SQL Server, MySQL, Oracle, PostgreSQL, SQLite	Yes	Yes	Windows GUI	Paid (Professional ~$185, Enterprise ~$266)
Liquibase	All major RDBMS + NoSQL	Yes	Limited (Pro)	Cross-platform CLI	Free (Community) / Paid (Pro)
Bytebase	MySQL, PostgreSQL, TiDB, ClickHouse, Oracle, SQL Server	Yes	No	Self-hosted / Cloud	Free (Community) / Paid (Pro)
DBDiff	MySQL, PostgreSQL, SQLite	Yes	No	Cross-platform CLI	Free (open-source)
DataFold data-diff	All major RDBMS + Snowflake, BigQuery, Redshift	No	Yes	Python CLI / Cloud	Free (OSS) / Paid (Cloud)
EMS DB Comparer	SQL Server, MySQL, PostgreSQL, Oracle	Yes	Yes	Windows GUI	Paid (~$95–$195)
ApexSQL Diff (Quest)	SQL Server	Yes	Yes (ApexSQL Data Diff)	Windows GUI + CLI	Paid (~$299+)
Beyond Compare	Any (via SQL file diff)	Via text diff	Via CSV diff	Windows / macOS / Linux GUI	Paid ($35–$70 one-time)
Diff Checker Pro	Any (SQL dump text / CSV export)	Via text diff	Via CSV diff	Browser extension	Free

Best for SQL Server

Redgate SQL Compare

Redgate SQL Compare is the industry benchmark for SQL Server schema comparison. Its object-level diffing covers tables, views, stored procedures, functions, triggers, and security principals. The UI presents a three-pane diff (left, right, delta script) that is immediately readable. The CLI integration means SQL Compare slots into Azure DevOps, GitHub Actions, and Jenkins pipelines with a single command. Redgate SQL Data Compare is sold separately and adds row-level data diffing.

Tradeoffs: SQL Server only. Pricing starts around $595/year per user for the full suite. If your team manages multiple database engines, you will need separate tools for each — an expensive proposition.

ApexSQL Diff (Quest)

ApexSQL Diff, now under the Quest Software umbrella, offers comparable schema comparison quality at a lower entry price (~$299 one-time). It handles all SQL Server objects including linked servers and SQL Server Agent jobs. The source control integration (Git, SVN, TFS) is mature. ApexSQL Data Diff is the paired data comparison module.

Tradeoffs: SQL Server only. Windows-only client. Quest's acquisition has slowed UI modernization compared to Redgate.

Microsoft SSDT / SqlPackage (Free)

Microsoft's own database compare utility is available as part of SQL Server Data Tools (SSDT) in Visual Studio and as the standalone SqlPackage CLI. The DeployReport and DriftReport actions produce XML diff reports comparing a .dacpac snapshot against a live database or another .dacpac. The tool is free, cross-platform (the CLI runs on Linux and macOS), and authoritative — it is the same engine Azure SQL Database uses internally for schema deployments.

# Export a .dacpac snapshot from production
SqlPackage /Action:Extract /SourceConnectionString:"Server=prod-db;..." /TargetFile:prod.dacpac

# Generate a drift report comparing snapshot against staging
SqlPackage /Action:DriftReport /TargetConnectionString:"Server=staging-db;..." /SourceFile:prod.dacpac /OutputPath:drift-report.xml

Tradeoffs: Schema comparison only — no data comparison. XML output requires post-processing for human readability. No GUI for schema diff (Visual Studio's Schema Compare adds a GUI layer but requires a VS license).

Best for MySQL & PostgreSQL

dbForge Schema Compare & Data Compare (Devart)

Devart's dbForge product line ships separate Schema Compare and Data Compare modules for both MySQL and PostgreSQL. The tools are among the most feature-complete available: object-level filtering, custom comparison keys for tables without primary keys, detailed HTML/Excel comparison reports, and one-click synchronization script generation with preview. dbForge integrates with Visual Studio and supports command-line automation via a scripting interface.

For MySQL-specific detail including side-by-side tool comparisons and CLI examples using mysqldump, see the dedicated MySQL database compare tool guide.

Tradeoffs: Windows-only client. Licensing per module can add up for teams needing both schema and data comparison across multiple database types.

DBDiff (open-source)

DBDiff is a lightweight open-source CLI tool (PHP-based) that connects to two MySQL or PostgreSQL databases, computes schema differences, and outputs migration SQL. It handles the tricky cases: column renames, index changes, constraint modifications. The output is clean, minimal SQL ready to pipe into your deployment workflow.

# Compare two MySQL databases
dbdiff --source="mysql://user:pass@host1:3306/db_staging" \
       --target="mysql://user:pass@host2:3306/db_production" \
       --output=migration.sql

# For PostgreSQL
dbdiff --source="postgres://user:pass@host1:5432/db_staging" \
       --target="postgres://user:pass@host2:5432/db_production"

Tradeoffs: Schema comparison only. No GUI, no data comparison, no sync automation. If your workflow is already CLI-centric, this is often sufficient.

Liquibase

Liquibase is primarily a database migration management tool, but its diff and diffChangeLog commands make it a capable database diff engine. The diff command reports structural differences to the console; the diffChangeLog command outputs them as a versioned Liquibase changelog ready for deployment. Liquibase supports MySQL, PostgreSQL, Oracle, SQL Server, SQLite, and others via JDBC drivers.

# Show schema diff between two databases
liquibase \
  --url="jdbc:mysql://staging-host:3306/app_db" \
  --referenceUrl="jdbc:mysql://prod-host:3306/app_db" \
  --username=dbuser --password=secret \
  diff

# Export diff as a deployable changelog
liquibase \
  --url="jdbc:mysql://staging-host:3306/app_db" \
  --referenceUrl="jdbc:mysql://prod-host:3306/app_db" \
  diffChangeLog \
  --changeLogFile=pending-changes.xml

Tradeoffs: The diff command is schema-focused; row-level data diff requires Liquibase Pro. The tool has a learning curve if you are not already using Liquibase for migrations, and JDBC configuration can be fiddly on first setup.

Best for Oracle, MongoDB & NoSQL

dbForge for Oracle

Devart extends its dbForge product line to Oracle with dedicated Schema Compare and Data Compare tools. They support Oracle-specific objects: packages, types, sequences, synonyms, database links, and materialized views. The synchronization engine correctly handles Oracle's ordered DDL requirements. This is the most complete GUI-based Oracle database compare software available outside Oracle's own tooling.

Altova DiffDog

Altova DiffDog differentiates itself by supporting cross-vendor database comparison: you can compare a PostgreSQL schema against an Oracle schema, or a SQL Server table against a MySQL table, and review the structural differences. It also handles XML and JSON structure comparison, making it useful for teams that store configuration in a database alongside their relational schema. For XML schema work specifically, our XML compare guide covers file-level diffing.

Tradeoffs: The cross-vendor comparison is useful for planning migrations but cannot generate a synchronization script across different database engines (the dialects are incompatible). Pricing ranges from ~$185 (Professional Edition) to ~$266 (Enterprise Edition); it is not a free tool.

MongoDB & document stores

MongoDB and other document databases present a fundamentally different challenge. There is no fixed schema to diff. The meaningful comparison modes are: collection-level document diff (comparing the shape and content of documents), index comparison, and schema validation rule comparison (if you use MongoDB schema validation). No standalone open-source tool handles all three cleanly as of 2026.

The practical approach for most teams is: export collections as JSON and use a data comparison tool that handles JSON structure natively. For comparing JSON config blobs or API response payloads stored in a document store, see the guide on comparing JSON objects online.

Free & Open-Source Database Compare Software

If budget is the primary constraint, the free and open-source options have improved substantially. The gap between paid and free tools is narrower today than it was three years ago — particularly for schema comparison.

DataFold data-diff (archived)

DataFold's open-source data-diff library was the strongest free option for data comparison. Written in Python, it used a divide-and-conquer checksum algorithm that made it efficient even on large tables. It supported MySQL, PostgreSQL, Oracle, Snowflake, BigQuery, Redshift, DuckDB, and more. The tool was designed for data validation pipelines: run it after an ETL job to verify row counts and checksums without exporting full datasets.

Note: Project Archived (May 2024). Datafold archived the public GitHub repository in May 2024. The open-source version is no longer actively maintained. Datafold now offers data comparison capabilities through their commercial Datafold Cloud platform only.

# Install
pip install data-diff

# Compare a table between staging and production (PostgreSQL)
data-diff \
  "postgresql://user:pass@staging-host/app_db" orders \
  "postgresql://user:pass@prod-host/app_db" orders \
  -k order_id \
  --columns order_total,status,updated_at

Tradeoffs: Data comparison only — no schema diff. Requires Python environment setup. Complex joins or custom comparison logic need scripting.

Microsoft SqlPackage (free, cross-platform)

Already covered in the SQL Server section, but worth emphasizing: SqlPackage is genuinely free, runs on Linux, macOS, and Windows, and produces authoritative schema comparison output for SQL Server and Azure SQL. For teams with SQL Server in their stack who cannot justify Redgate licensing, SqlPackage covers the schema diff use case at zero cost.

Bytebase Community Edition

Bytebase is a schema change management platform (think Liquibase with a web UI). The Community Edition is free and self-hosted. It provides schema diff between migration versions, change review workflow, and basic drift detection. It does not do data comparison. Where Bytebase excels is team collaboration: multiple reviewers can approve a schema change before it deploys, with a full audit trail. For organizations graduating from ad-hoc migration scripts to a governed process, Bytebase is the most approachable free starting point.

How to Compare Databases Without Locking Production

Connecting a database comparer directly to a live production database is risky. Most GUI tools open a persistent connection and may issue metadata queries that cause brief lock contention on busy systems. For data comparison, full-table scans on multi-million-row tables can saturate I/O. The following strategies let you run a complete db compare safely.

Strategy 1: Schema-only export (safest)

For schema comparison, never connect the tool directly to production. Instead, export a schema snapshot to a SQL file and diff the files. Schema exports are read-only, typically complete in seconds, and produce no lock contention.

# MySQL: export schema only (no data, no comments)
mysqldump --no-data --skip-comments --single-transaction \
  -u root -p production_db > prod_schema.sql

mysqldump --no-data --skip-comments \
  -u root -p staging_db > staging_schema.sql

# Compare the SQL files
diff prod_schema.sql staging_schema.sql

# PostgreSQL: export schema only
pg_dump --schema-only --no-comments \
  -U postgres production_db > prod_schema.sql

pg_dump --schema-only --no-comments \
  -U postgres staging_db > staging_schema.sql

See the official pg_dump documentation and the mysqldump reference for the complete flag list — both tools ship with their respective database servers and require no extra installation.

Once you have the exported SQL files, you can compare them with any text diff tool — including Linux command-line comparison tools or a browser-based tool like Diff Checker Pro (which handles SQL files with syntax highlighting and handles files up to 10 MB in the browser without any server upload).

Strategy 2: Read replica for data comparison

For data comparison, connect your data comparison tools to a read replica rather than the primary. Most cloud database services (RDS, Cloud SQL, Azure Database) provide replicas. The replica is always slightly behind primary (replication lag), which is acceptable for most comparison use cases — you are detecting systematic differences, not sub-second deltas.

Strategy 3: Snapshot-based comparison

Take a cold snapshot (RDS snapshot, LVM snapshot, or pg_basebackup) of production, restore it to a temporary comparison instance, and run all comparison operations against that instance. Zero lock risk on production. The comparison instance can be torn down after the run. This approach is standard for compliance audits where you need a point-in-time accurate diff.

Strategy 4: Off-peak scheduling

For tools that must connect to production directly (some schema inspection queries are hard to avoid), schedule comparison jobs during off-peak hours. Tools like Liquibase, DBDiff, and DataFold's data-diff all support cron-friendly CLI execution. Log the output and review it the next morning rather than running interactive comparisons during business hours.

Database Diff in CI/CD Pipelines

Integrating a database diff step into your CI/CD pipeline is the highest-value workflow change most teams can make. It converts database comparison from a manual pre-release checklist item into an automated gate that blocks bad deployments before they reach production.

Pattern: Liquibase diff in GitHub Actions

name: Database Schema Drift Check

on:
  pull_request:
    paths:
      - 'db/migrations/**'

jobs:
  schema-diff:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Install Liquibase
        run: |
          curl -L https://github.com/liquibase/liquibase/releases/download/v4.27.0/liquibase-4.27.0.tar.gz | tar xz
          echo "$(pwd)/liquibase-4.27.0" >> $GITHUB_PATH

      - name: Run schema diff
        run: |
          liquibase \
            --url="jdbc:postgresql://${{ secrets.STAGING_DB_HOST }}:5432/app_db" \
            --referenceUrl="jdbc:postgresql://${{ secrets.PROD_SNAPSHOT_HOST }}:5432/app_db" \
            --username=${{ secrets.DB_USER }} \
            --password=${{ secrets.DB_PASS }} \
            diff 2>&1 | tee diff-output.txt
          # Fail the job if unexpected differences are found
          grep -q "Unexpected differences" diff-output.txt && exit 1 || exit 0

Pattern: SqlPackage drift report in Azure DevOps

# azure-pipelines.yml (simplified)
- task: SqlAzureDacpacDeployment@1
  displayName: 'Generate Schema Drift Report'
  inputs:
    azureSubscription: 'prod-connection'
    AuthenticationType: 'connectionString'
    ConnectionString: '$(ProdConnectionString)'
    deployType: 'DriftReport'
    GenerateDropsInScript: false
    ReportPath: '$(Build.ArtifactStagingDirectory)/drift-report.xml'

Pattern: data-diff as a post-deployment data validation step

#!/bin/bash
# post-deploy-validation.sh
# Run after data migration; fail pipeline if row counts diverge

data-diff \
  "postgresql://user:pass@source-host/app_db" orders \
  "postgresql://user:pass@target-host/app_db" orders \
  -k order_id \
  --stats \
  --where "created_at > '2026-01-01'" \
  2>&1 | tee data-diff-report.txt

DIFF_COUNT=$(grep -oP '(?<=rows differ: )\d+' data-diff-report.txt || echo 0)
if [ "$DIFF_COUNT" -gt "0" ]; then
  echo "ERROR: $DIFF_COUNT rows differ after migration"
  exit 1
fi
echo "Data validation passed"

For teams adopting version-controlled database changes as part of a broader DevOps workflow, combining Liquibase (schema versioning), data-diff (post-migration validation), and a browser-based tool like Diff Checker Pro for quick ad-hoc SQL file review covers the full lifecycle without overbuying tooling.

How to Choose: Decision Matrix by Use Case

No single db comparison tool is universally best. The right pick depends on four variables: database engine, comparison mode needed, team workflow (GUI vs. CLI vs. pipeline), and budget. Use the matrix below to shortlist candidates, then evaluate the top one or two against your specific schema complexity and data volumes.

Use Case	Primary Recommendation	Free Alternative
SQL Server schema diff (GUI, Windows team)	Redgate SQL Compare	SSDT / SqlPackage
SQL Server data diff (GUI)	Redgate SQL Data Compare	ApexSQL Data Diff (trial)
MySQL schema diff (GUI)	dbForge Schema Compare for MySQL	MySQL Workbench Sync Wizard
PostgreSQL schema diff (CLI / CI)	Liquibase Community	DBDiff
Multi-engine schema diff (one tool)	Altova DiffDog	Liquibase Community
Data validation after ETL / migration	DataFold data-diff (OSS)	DataFold data-diff (OSS)
CI/CD pipeline database gate	Liquibase + GitHub Actions	DBDiff + diff CLI
Team schema change governance + audit trail	Bytebase (Community or Pro)	Bytebase Community
Quick review of mysqldump / pg_dump output	Diff Checker Pro (browser)	Diff Checker Pro (free)
VS Code-based SQL file diff workflow	VS Code built-in diff	See VS Code compare guide
Oracle schema diff	dbForge Schema Compare for Oracle	Liquibase Community
SQL script / query text diff	Diff Checker Pro / Beyond Compare	See SQL compare guide

Budget tiers at a glance

• $0: SqlPackage (SQL Server schema), Liquibase Community (multi-engine schema), DBDiff (MySQL/PG schema), data-diff (data validation), Bytebase Community (governance), Diff Checker Pro (SQL text / CSV diff)
• $35–$200: Beyond Compare ($35–$70 perpetual), Altova DiffDog (Professional ~$185, Enterprise ~$266), EMS DB Comparer (~$95–$195 per DB)
• $299–$600+/yr: ApexSQL Diff (~$299), dbForge suites, Redgate SQL Compare (~$595/yr), Liquibase Pro

Teams comparing only SQL script files — schema exports, migration scripts, or mysqldump text output — do not need a dedicated database client tool at all. A text diff tool that understands SQL syntax is sufficient for the review step. For terminal-based workflows, see the guide to diff in Unix for combining mysqldump --no-data exports with shell diff tooling.

Frequently Asked Questions

What is the difference between database comparison and database synchronization?

Comparison identifies differences between two database states and presents them as a report or visual diff. Synchronization goes a step further: it generates and optionally executes the DDL or DML statements required to make one database match the other. Most database compare software bundles both capabilities — you compare first to review what will change, then choose to synchronize or export the script for manual review. Never skip the comparison review step before synchronizing toward production.

Can I compare databases across different engines, such as MySQL to PostgreSQL?

Most database comparer tools only compare two instances of the same database engine because they use engine-specific metadata queries. Altova DiffDog is the notable exception: it supports cross-engine structural comparison. However, even DiffDog cannot generate a synchronization script across engines — the SQL dialects are incompatible. Cross-engine comparison is primarily useful for planning a migration, not automating one.

Which database comparison tool is free?

Several strong free options exist: Microsoft SqlPackage (SQL Server / Azure SQL schema diff, cross-platform), Liquibase Community Edition (multi-engine schema diff, CI/CD ready), DBDiff (MySQL and PostgreSQL schema diff, CLI), and Bytebase Community (schema governance with web UI). Diff Checker Pro is also free and handles SQL dump files and exported CSVs as plain text with SQL syntax highlighting — useful for quick ad-hoc reviews without installing a database client. Note: DataFold's data-diff library was archived in May 2024 and is no longer actively maintained; Datafold now offers data diffing through their commercial cloud platform only.

How do I compare large databases without locking production?

The safest pattern is to export a schema snapshot with mysqldump --no-data or pg_dump --schema-only and compare the exported SQL files rather than connecting tools directly to production. For data comparison, connect to a read replica or a cold snapshot restored to a temporary instance. Schedule comparison jobs during off-peak windows and use read-only database credentials. Never run a full-table data comparison against a primary production instance during business hours.

Can a database comparison tool work in CI/CD pipelines?

Yes. Liquibase, DBDiff, SqlPackage, and DataFold data-diff all expose CLI interfaces designed for pipeline integration. Liquibase's diff command returns a non-zero exit code if unexpected differences are found, making it a natural pipeline gate. GitHub Actions, Jenkins, GitLab CI, and Azure DevOps all have documented examples of Liquibase and SqlPackage integration. The database diff step typically runs after the migration script is applied to a staging environment and before promotion to production is approved.

Is database comparison the same as data validation?

There is overlap but the goals differ. Database comparison identifies structural and content differences between two database states — the question is "how do these two databases differ?" Data validation checks whether data meets quality constraints — the question is "does this data conform to expected rules, ranges, or referential integrity?" Tools like DataFold's data-diff sit at the intersection: they compare row content between databases (comparison) but are commonly used to verify that a migration preserved data integrity (validation). Most dedicated data comparison tools focus on the comparison side; data quality platforms (Great Expectations, dbt tests) handle validation.

Does Diff Checker Pro connect to databases directly?

No. Diff Checker Pro is a browser-based text diff extension built on the Monaco DiffEditor (the same engine that powers VS Code). It does not have a database client or JDBC driver. Its role in a database workflow is comparing the text output of database tools: mysqldump --no-data schema exports, pg_dump schema dumps, exported CSVs, or copy-pasted SQL scripts. It auto-detects SQL syntax for highlighting, supports split and unified diff views, handles files via drag-and-drop (TXT, CSV, SQL as plain text), and uses three diff algorithms including Smart Diff and Ignore Whitespace. For teams reviewing schema exports or SQL migration files, it is a fast, zero-install review layer — not a replacement for a dedicated db comparison tool with native database connectivity.