MySQL is a relational database using structured SQL queries and ACID transactions, while MongoDB is a NoSQL document database using flexible JSON-like documents. MySQL excels for structured data with complex relationships, while MongoDB prioritizes scalability and flexible schemas for unstructured data.
MySQL vs MongoDB — Side-by-side comparison on A Versus B
Open-source relational SQL database with ACID compliance and mature ecosystem
Open-source NoSQL document database with flexible schemas and native horizontal scaling
Data Model. Query Language. Schema Flexibility. Horizontal Scalability. ACID Transactions. Learning Curve. Read Performance (simple queries)
Choose MySQL if you have structured data with complex relationships, require strict ACID compliance across transactions, or need established enterprise support with minimal learning curve. Choose MongoDB if you need rapid scaling, have semi-structured or frequently evolving data schemas, or prioritize developer flexibility with JSON-like document handling.
MySQL: Partial (InnoDB only) | MongoDB: N/A
MySQL: ~28,000 (MySQL 8.4) | MongoDB: N/A
MySQL: ~450 (5-table join) | MongoDB: N/A
MySQL: JSON functions only | MongoDB: N/A
MySQL: ~80 (minimal config) | MongoDB: N/A
MySQL: Via third-party extensions | MongoDB: N/A
MySQL: Limited, basic support | MongoDB: N/A
MySQL: Standard table partitioning | MongoDB: N/A
MySQL: $13.50 (MySQL 8.4) | MongoDB: N/A
MySQL: 5 (8.0-8.4 active) | MongoDB: N/A
MySQL: Oracle, multiple vendors | MongoDB: N/A
MySQL: 151 (default, configurable) | MongoDB: N/A
MySQL: Yes - master-slave, group replication | MongoDB: N/A
MySQL: 5-50 ms (indexed queries) | MongoDB: N/A
MySQL: Full ACID across multiple tables (since v5.7) | MongoDB: Multi-document ACID (since v4.0, snapshot isolation)
MySQL: Manual sharding (theoretical unlimited) | MongoDB: Native automatic sharding across nodes
MySQL: Fixed schema, requires migration for changes | MongoDB: Schema-less (dynamic fields)
MySQL: 3-5ms for simple queries | MongoDB: 8-12ms for equivalent queries
MySQL: 8-12GB working set | MongoDB: 24-36GB working set
MySQL: 25+ years (MySQL 1.0 released 1995) | MongoDB: 19 years (MongoDB 1.0 released 2009)
MySQL: 46% of web applications (Stack Overflow 2024) | MongoDB: 28% of web applications (Stack Overflow 2024)
MySQL: $50-200 (self-hosted) | MongoDB: N/A
MySQL: Manual configuration required | MongoDB: N/A
MySQL: Third-party tools only | MongoDB: N/A
MySQL: 64TB (hardware dependent) | MongoDB: N/A
MySQL: Unlimited (with sharding complexity) | MongoDB: N/A
MySQL: User-dependent (no guarantee) | MongoDB: N/A
MySQL: 5+ (on-prem, cloud, edge, containers, hybrid) | MongoDB: N/A
MySQL: 2 (InnoDB, MyISAM) | MongoDB: N/A
MySQL: $2,500-$50,000 (Oracle) | MongoDB: N/A
Complex Analytical Query Speed (with JOINs + aggregations)
MySQL: 850ms (without window functions) | MongoDB: N/A
Annual Enterprise Support Cost (per server)
MySQL: 64MB (practical limit) | MongoDB: N/A
MySQL: 1-2 (English mainly) | MongoDB: N/A
Complex Analytical Query Speed (Aggregate + Join)
MySQL: Yes, since 5.7 (basic operations only) | MongoDB: N/A
MySQL: Basic (limited language support, no stemming) | MongoDB: N/A
MySQL: Since 8.0 (limited implementation) | MongoDB: N/A
MySQL: 100+ simultaneous users | MongoDB: N/A
MySQL: 15-30 minutes (server setup required) | MongoDB: N/A
MySQL: 140 TB theoretical | MongoDB: N/A
MySQL: Remote access via TCP/IP | MongoDB: N/A
MySQL: Role-based access control (RBAC) with 5+ permission levels | MongoDB: N/A
MySQL: 5-15 ms (network latency included) | MongoDB: N/A
MySQL: ~3 months (quarterly) | MongoDB: N/A
MySQL: 1 (InnoDB primary) | MongoDB: N/A
MySQL: Full MSI installer, native support | MongoDB: N/A
MySQL: Reference implementation | MongoDB: N/A
MySQL: Requires manual setup | MongoDB: N/A
MySQL: Manual (30-60+ minutes) | MongoDB: N/A
MySQL: 1 (self-managed: 2-3 typical) | MongoDB: N/A
Minimum Monthly Operational Cost (production-ready)
MySQL: $0 (software) + infrastructure costs | MongoDB: N/A
MySQL: Depends on hardware (typically 1-10TB) | MongoDB: N/A
MySQL: 4-24 (server provisioning + config) | MongoDB: N/A
MySQL: None (depends on your infrastructure) | MongoDB: N/A
MySQL: 1-10 TB (single server) | MongoDB: Petabytes (with sharding)
MySQL: Native since v5.0 (2008) | MongoDB: Added in v4.0 (2018)
MySQL: N/A | MongoDB: 50,000-100,000 docs/sec
MySQL: N/A | MongoDB: ACID from v4.0 (slower than PostgreSQL)
Query Language Complexity (learning curve)
MySQL: N/A | MongoDB: 2-4 weeks (MongoDB Query Language simpler syntax)
MySQL: N/A | MongoDB: MongoDB Atlas managed cloud (SaaS); community edition free
MySQL: N/A | MongoDB: 10+ (single field, compound, geospatial, text, wildcard)
MySQL: N/A | MongoDB: 0 GB (Atlas free tier discontinued)
MySQL: N/A | MongoDB: Multi-document (v4.0+)
MySQL: N/A | MongoDB: Unlimited (sharding dependent)
MySQL: N/A | MongoDB: MongoDB Query Language (MQL)
MySQL: N/A | MongoDB: Manual sharding + Atlas auto-scaling
MySQL: N/A | MongoDB: Not enforced natively
MySQL: N/A | MongoDB: 200+ query operators, joins, aggregation pipeline
MySQL: N/A | MongoDB: 5-10ms (cluster dependent)
MySQL: N/A | MongoDB: $57 (M10 Atlas cluster)
MySQL: N/A | MongoDB: Multi-document ACID across collections
MySQL: N/A | MongoDB: Manual sharding configuration required
MySQL: N/A | MongoDB: 10,000-50,000 ops/sec
MySQL: N/A | MongoDB: Moderate to high (backups, sharding, monitoring)
Query Complexity (Aggregation Capability)
MySQL: N/A | MongoDB: 9 (full aggregation pipeline)
MySQL: N/A | MongoDB: Unlimited (scales with cluster)
MySQL: N/A | MongoDB: 5-10 days (custom code)
MySQL: N/A | MongoDB: No (third-party only)
MySQL: N/A | MongoDB: Change Streams (enterprise feature)
MySQL: N/A | MongoDB: Unlimited (sharding across clusters)
MySQL: N/A | MongoDB: High (infrastructure management needed)
MySQL: N/A | MongoDB: 38 ms (indexed query)
MySQL: N/A | MongoDB: Manual API layer required
MySQL: N/A | MongoDB: ~50,000 (sharded cluster)
MySQL: N/A | MongoDB: Multi-document (v4.0+, with limitations)
Storage Overhead (vs Equivalent Relational)
MySQL: N/A | MongoDB: 2-3x larger (denormalization)
MySQL: N/A | MongoDB: Yes (automatic sharding)
MySQL: N/A | MongoDB: Aggregation pipeline (moderate for complex queries)
MySQL: N/A | MongoDB: Optional/flexible (schema-on-read)
MySQL: N/A | MongoDB: 4-8 hours (managed cloud option available)
MySQL: N/A | MongoDB: MQL (simpler for simple queries, steeper for complex joins)
MySQL: N/A | MongoDB: Multi-document transactions (4.0+)
MySQL: N/A | MongoDB: Native, automatic shard distribution
MySQL: N/A | MongoDB: 25-40% (document format, field duplication)
MySQL: N/A | MongoDB: 8-15+ seconds ($lookup)
MySQL: N/A | MongoDB: Limited (core features only)
MySQL vs MongoDB — Structured Comparison Data
Machine-readable comparison dataset for MySQL vs MongoDB. Contains 146 attribute comparisons, 5 FAQ pairs.
MySQL vs MongoDB — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for MySQL vs MongoDB.
Should I use MongoDB or MySQL for my new project?
Use MySQL if you have well-defined, structured data with clear relationships (e.g., user accounts, orders, inventory). Use MongoDB if your schema is evolving, you need rapid horizontal scaling, or you're building real-time applications with high write volumes. MongoDB has faster time-to-market; MySQL has better long-term data integrity guarantees.
Can MongoDB handle complex queries like SQL JOINs?
MongoDB can perform lookups across collections using the $lookup aggregation operator, but they are 5-10x slower than native SQL JOINs. If your queries involve frequent multi-table joins, MySQL is the better choice. MongoDB excels when related data is embedded within documents, eliminating the need for joins.
Is MongoDB better for scalability than MySQL?
Yes, MongoDB's automatic sharding makes horizontal scaling significantly easier. Sharding MySQL requires manual partitioning, careful key selection, and application-level routing logic. MongoDB handles sharding transparently. However, at massive scale (petabyte+), both have proven viable; the difference is operational complexity.
MySQL typically has lower hardware costs due to efficient memory usage and mature optimization. MongoDB requires 2-3x more RAM for equivalent datasets but may reduce operational overhead through automatic scaling. Cloud hosting costs favor MySQL for small/medium workloads; MongoDB wins for workloads needing frequent scaling.
Can I migrate from MongoDB to MySQL or vice versa?
Migration is possible but complex. MongoDB→MySQL requires flattening nested documents into normalized tables, often causing data loss or requiring significant transformation. MySQL→MongoDB is easier since denormalization is natural. Plan your database choice upfront; mid-project migration is costly and risky.
Data Model: MySQL has Relational (tables, rows, columns), while MongoDB has Document-based (JSON/BSON documents).
Query Language: MySQL has SQL (Structured Query Language), while MongoDB has MongoDB Query Language (MQL).
Schema Flexibility: MySQL has Fixed schema required, while MongoDB has Dynamic schema (schema-less).
Horizontal Scalability: MySQL has Complex sharding, limited native support, while MongoDB has Built-in sharding, native horizontal scaling.
ACID Transactions: MySQL has Full ACID support across tables, while MongoDB has Multi-document ACID (MongoDB 4.0+).
Learning Curve: MySQL has Easier for developers familiar with SQL, while MongoDB has Easier for developers familiar with JSON/JavaScript.
Consider: Read Performance (simple queries)
Read Performance (simple queries): MySQL has Highly optimized for structured queries, while MongoDB has Good for nested document retrieval.