Company Overview
InfluxDB is developed and maintained by InfluxData. Founded in 2013 by Paul Dix, Todd Persen, and John Shahid, InfluxData is headquartered in San Francisco, California, USA. InfluxDB is the world's leading time-series database, purpose-built for monitoring, IoT, real-time analytics, and high-precision observability.
InfluxDB features a columnar storage architecture deeply optimized for timestamped data, supporting millions of data points per second in writes, efficient compression, and sub-second query responses. The product portfolio spans open-source self-managed deployments, fully-managed cloud services, and edge deployments, with both SQL and Flux query support, connected to 400+ data sources through the Telegraf agent ecosystem.
Related categories:
- ποΈ Database Services β Browse more database products
- π Monitoring Services β Explore monitoring and observability solutions
Key Milestones
| Year | Milestone |
|---|---|
| 2013 | Founded by Paul Dix and team, began developing the time-series database |
| 2014 | Released first open-source version of InfluxDB, quickly gaining developer traction |
| 2015 | Launched Telegraf (data collection agent) and Kapacitor (data processing framework) |
| 2018 | Released InfluxDB 2.0 public beta with Flux query language and unified UI |
| 2020 | Launched InfluxDB Cloud, a fully-managed serverless time-series database service |
| 2021 | Introduced InfluxDB IOx engine (Rust + Apache Arrow), foundation for 3.0 |
| 2023 | Released InfluxDB 3.0, rewritten in Rust, supporting SQL + Flux + InfluxQL |
| 2024 | Launched InfluxDB Cloud Dedicated and Cloud Serverless dual modes |
| 2025 | Surpassed 1 billion downloads; Telegraf downloads exceeded 5 billion |
| 2026 | Continues to lead the time-series database market, ranked #1 by DB-Engines |
Product Portfolio
ποΈ Time-Series Database
| Product | Description |
|---|---|
| InfluxDB 3.0 Enterprise | Enterprise self-managed time-series DB, built on Rust + Apache Arrow |
| InfluxDB Cloud Serverless | Fully-managed serverless time-series DB, pay-as-you-go, auto-scaling |
| InfluxDB Cloud Dedicated | Dedicated cluster cloud DB for high performance and isolation |
| InfluxDB OSS | Open-source version for development and self-managed deployments |
| InfluxDB 1.x | Classic version, maintained for legacy application compatibility |
π Data Collection & Integration
| Product | Description |
|---|---|
| Telegraf | Open-source data collection agent with 400+ plugins for metrics and events |
| Telegraf Enterprise | Enterprise agent with enhanced management, security, and reliability |
| Client Libraries | SDKs for Python, JavaScript, Go, Java, C#, and more |
| Integrations | Deep integration with Grafana, Kubernetes, AWS, Azure, GCP |
π Query & Analytics
| Product | Description |
|---|---|
| SQL | Native standard SQL support in InfluxDB 3.0 |
| Flux | Powerful functional query language for data pipelines and transformations |
| InfluxQL | SQL-like query language compatible with InfluxDB 1.x |
| Dashboards & Visualization | Built-in dashboards and charts with customizable visualization |
Core Strengths
π #1 Time-Series Database
InfluxDB has consistently ranked #1 in DB-Engines Time Series DB rankings, with 1B+ downloads, 1M+ active open-source instances, and 2,800+ open-source contributors. Global enterprises including Honeywell, Rocket Lab, Intuit, NVIDIA, Siemens, and Salesforce rely on InfluxDB.
β‘ Extreme Write & Query Performance
InfluxDB 3.0, rewritten in Rust with Apache Arrow columnar in-memory format, supports millions of data points per second in writes with millisecond-level query latency. Compression ratios reach 10:1 to 30:1, significantly reducing storage costs.
π Edge-to-Cloud Continuity
InfluxDB provides a unified data pipeline from edge to cloud: run InfluxDB OSS at the edge for real-time data collection, automatically sync to InfluxDB Cloud for centralized analysis, without redesigning your pipeline.
π Rich Open-Source Ecosystem
Telegraf features 400+ plugins connecting to Kafka, Prometheus, Syslog, MQTT, Docker, Kubernetes, and more. Deep integration with Grafana provides rich observability visualization capabilities.
Competitive Landscape
| Competitor | Type | Key Difference |
|---|---|---|
| Prometheus | Open-source monitoring + TSDB | Emphasis on Pull model and alerting; lacks persistent storage and high-cardinality handling |
| TimescaleDB | PostgreSQL-based time-series DB | SQL-compatible, but write performance and compression below InfluxDB 3.0 |
| VictoriaMetrics | Open-source high-performance TSDB | Lightweight, PromQL-compatible, but less feature-rich than InfluxDB |
| QuestDB | Open-source high-performance TSDB | Emphasizes low-latency SQL, but weaker ecosystem and integrations |
| ClickHouse | Columnar analytics database | Suitable for OLAP analytics, but less optimized for time-series writes |
| Datadog | SaaS observability platform | Fully-managed, but higher cost and no self-control over data |
Summary
As the benchmark in time-series databases, InfluxDB's exceptional write performance, flexible deployment options, and rich open-source ecosystem make it the database of choice for monitoring, IoT, observability, and real-time analytics. The InfluxDB 3.0 rewrite on Rust + Apache Arrow further cements its technological leadership, positioning it strongly in emerging fields such as physical AI, industrial IoT, and edge computing.