TimescaleDB vs Influxdb: Which is Better in 2026?
Choosing between TimescaleDB and Influxdb comes down to understanding what each tool does best. This comparison breaks down the key differences so you can make an informed decision based on your specific needs, not marketing claims.
Bottom line: TimescaleDB wins this matchup. PostgreSQL is our overall Data & Databases pick. PostgreSQL is our free Data & Databases pick. Pick Influxdb if you need a free tier to start with.
Short on time? Here's the quick answer
Based on published vendor pricing and features and on public review data, here's who should pick what:
TimescaleDB
Time series database on PostgreSQL
Best for you if:
- • You want PostgreSQL extension
Influxdb
High-speed time-series database for real-time analytics
Best for you if:
- • You want purpose-built time-series
| At a Glance | ||
|---|---|---|
Starts at | Free Free plan | Free Free plan |
Category | Data & Databases Analytics | Data & Databases Analytics |
Rating | 4.6/5 G2 4.6 114 reviews | 4.5/5 G2 4.5 102 reviews |
Free plan | Yes | Yes |
Watch out for | Cloud tier storage/compute beyond base limits | High ingestion rates can rapidly increase Cloud Serverless costs. |
Choose TimescaleDB or Influxdb?
Choose TimescaleDB if
- You want PostgreSQL extension
- You want time series optimized
Choose Influxdb if
- You want purpose-built time-series
- You want good performance
In-Depth Analysis
TimescaleDB
Time series database on PostgreSQL
TimescaleDB's pricing is quite generous, especially with the free self-hosted option offering full features.
Watch out
Cloud tier storage/compute beyond base limits
Strengths
- Pro: PostgreSQL extension
- Pro: Time series optimized
- Pro: Full SQL support
- Pro: Easy to start
- Pro: Good compression
Weaknesses
- Con: PostgreSQL required
- Con: Some features require a paid plan
- Con: Learning curve
- Con: Scaling complex
- Con: Resource usage
Key features
Influxdb
High-speed time-series database for real-time analytics
The Cloud Serverless (Paid) tier offers competitive usage-based pricing, though costs can scale quickly with high ingestion.
Watch out
High ingestion rates can rapidly increase Cloud Serverless costs.
Strengths
- Pro: Purpose-built time-series
- Pro: Good performance
- Pro: Telegraf integration
- Pro: Flux query language
- Pro: Cloud option
Weaknesses
- Con: Flux learning curve
- Con: Version confusion (1.x vs 2.x)
- Con: Expensive cloud
- Con: Cluster enterprise only
- Con: Schema design tricky
Key features
Pricing: TimescaleDB vs Influxdb
| Plan | TimescaleDB | Influxdb |
|---|---|---|
| Tier 1 | Free Self-hosted | Free Cloud Serverless (Free) |
| Tier 2 | $29 month Cloud | Cloud Serverless (Paid) |
| Tier 3 | N/A | Cloud Dedicated |
| Tier 4 | N/A | Free Core (OSS) |
| Tier 5 | N/A | Enterprise |
Pricing verified from each vendor's public pricing page. Compare in detail on TimescaleDB pricing and Influxdb pricing.
Key Takeaways
TimescaleDB
- Higher user rating: 4.6/5 vs 4.5/5
- Larger review base (114 reviews)
- Free tier available
- Our pick for this comparison
Influxdb
- Choose if you want high-speed time-series database for real-time analytics
The Bottom Line
TimescaleDB wins this matchup. PostgreSQL is our overall Data & Databases pick. PostgreSQL is our free Data & Databases pick.
Frequently Asked Questions
Is TimescaleDB or Influxdb better in 2026?
TimescaleDB wins this matchup. PostgreSQL is our overall Data & Databases pick. PostgreSQL is our free Data & Databases pick. Pick TimescaleDB for data & databases workflows (main strength: PostgreSQL extension). Pick Influxdb for data & databases workflows (main strength: purpose-built time-series).
What are TimescaleDB and Influxdb used for?
TimescaleDB: Time series database on PostgreSQL. Influxdb: High-speed time-series database for real-time analytics.
What does TimescaleDB cost vs Influxdb?
TimescaleDB's paid plans start at Free (Cloud). Influxdb pricing is on their site.
What's the main difference between TimescaleDB and Influxdb?
TimescaleDB's main strength: PostgreSQL extension. Influxdb's main strength: purpose-built time-series.