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

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

Key Differences

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

Feature

InfluxDB

Database

Apache Spark

Data Processing

Side-by-side comparison of developer tools
Scalable datastore for metrics, events, and real-time analytics
Unified analytics engine for large-scale data processing
GitHub Stars
⭐ 31,731
⭐ 43,909
Contributors
👥 695
👥 3,575
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
Rust
Scala
Features
  • • Database
  • • Go
  • • Influxdb
  • • Metrics
  • • Monitoring
  • • Big Data
  • • Java
  • • Jdbc
  • • Python
  • • R
Integrations
No integrations listed
No integrations listed
Momentum Score
44/100 (stable)
81/100 (stable)
Community Health
57/100 (moderate)
91/100 (excellent)
Maturity Index
59/100 (growing)
89/100 (mature)
Innovation Score
58/100 (progressive)
91/100 (pioneering)
Risk Score (higher is safer)
61/100 (low)
94/100 (minimal)
Developer Experience
53/100 (needs-improvement)
80/100 (good)
Links
🌐 Visit Website View on GitHub
🌐 Visit Website View on GitHub

InfluxDB Strengths

Apache Spark Strengths

  • ✓ More popular (43,909 stars)
  • ✓ Larger community (3,575 contributors)

When to Use InfluxDB vs Apache Spark

Use InfluxDB 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

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

More Comparisons

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Data source: GitHub API

Last updated: 8/30/2026