MySQL vs Apache Spark: Key Differences & When to Use Each

Comprehensive side-by-side comparison of features, pricing, and metrics

Key Differences

Compare MySQL and Apache Spark across features, pricing, integrations, and community metrics. MySQL / Apache Spark.

Feature

MySQL

Database

Apache Spark

Data Processing

Side-by-side comparison of developer tools
Open source relational database
Unified analytics engine for large-scale data processing
GitHub Stars
⭐ 12,253
⭐ 43,233
Contributors
👥 695
👥 3,432
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
C++
Scala
Features
  • • Open Source
  • • database
  • • Big Data
  • • Java
  • • Jdbc
  • • Python
  • • R
Integrations
  • • mysql
No integrations listed
Momentum Score
22/100 (stable)
79/100 (stable)
Community Health
57/100 (moderate)
91/100 (excellent)
Maturity Index
54/100 (emerging)
90/100 (mature)
Innovation Score
20/100 (traditional)
91/100 (pioneering)
Risk Score (higher is safer)
53/100 (low)
94/100 (minimal)
Developer Experience
18/100 (poor)
80/100 (good)
Links
🌐 Visit Website View on GitHub
🌐 Visit Website View on GitHub

MySQL Strengths

Apache Spark Strengths

  • ✓ More popular (43,233 stars)
  • ✓ Larger community (3,432 contributors)
  • ✓ More features (5 listed)

When to Use MySQL vs Apache Spark

Use MySQL when its strengths align better with your stack and team needs, and choose Apache Spark when its ecosystem, integrations, or cost profile is a better fit.

Related comparisons

MySQL vs Elasticsearch → Apache Spark vs Apache Flink → MySQL vs Redis → Apache Spark vs Apache Beam → MySQL vs ClickHouse → Apache Spark vs Elasticsearch → MySQL vs TiDB → Apache Spark vs Redis → MySQL vs CockroachDB → Apache Spark vs Grafana → MySQL vs InfluxDB → Apache Spark vs Prometheus →

More Comparisons

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Data source: GitHub API

Last updated: 5/5/2026