TDengine
TDengine is an open-source, high-performance time-series database optimized for IoT and industrial scenarios, capable of handling billions of data points at scale. It combines data ingestion, storage, and stream processing in a single system with built-in caching and AI-powered analytics features.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | taosdata/TDengine |
| Owner | taosdata |
| Primary language | C |
| License | AGPL-3.0 — OSI-approved |
| Stars | 25k |
| Forks | 5k |
| Open issues | 426 |
| Latest release | ver-3.4.1.6 (2026-04-30) |
| Last updated | 2026-07-08 |
| Source | https://github.com/taosdata/TDengine |
What TDengine is
Written in C with native distributed architecture, TDengine supports SQL queries, RAFT-based clustering, Kubernetes deployment, and compute-storage separation. It addresses high-cardinality workloads and includes built-in stream processing, data subscription, and agent-based AI integration.
Get the TDengine source
Clone the repository and explore it locally.
git clone https://github.com/taosdata/TDengine.gitcd TDengine# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- First build requires `-DBUILD_CONTRIB=ON` to download external dependencies (xxhash, zstd, lz4); subsequent builds can omit this flag. Linux is the primary build and deployment platform.
- Clustering and distributed setup require RAFT consensus and proper configuration for availability; test failover scenarios in staging before production deployment.
- AGPL-3.0 license requires legal review if integrating into proprietary systems or cloud SaaS offerings; modifications to core code trigger copyleft obligations.
- Memory and disk requirements scale with data volume and retention policy; monitoring and capacity planning are essential for large-scale deployments.
- AI agent (TDgpt) integration relies on external LLMs and foundation models; separate API keys, rate limits, and cost considerations apply.
When to avoid it — and what to weigh
- AGPL-3.0 license incompatibility with closed-source products — Any derivative works or modifications must be released under AGPL-3.0; organizations requiring proprietary modifications or integration into closed-source products must review licensing terms carefully or license separately.
- Windows-primary deployments — Open-source builds are primarily Linux/macOS; Windows support in the open-source tree is explicitly limited. Use Linux as the production target.
- Simple, single-node, low-scale deployments — TDengine's architecture complexity (clustering, RAFT, distribution) adds operational overhead; simpler single-node alternatives may be more appropriate for small, stateless, or non-critical use cases.
- Relational OLTP workloads — TDengine is purpose-built for time-series append-heavy workloads, not general-purpose transactional databases; complex JOINs, updates, and multi-entity relationships belong in a traditional RDBMS.
License & commercial use
Licensed under AGPL-3.0 (GNU Affero General Public License v3.0). Core modules including clustering and AI agent are open-source under this license. AGPL-3.0 is a copyleft license requiring derivative works and network-based service deployments to be released under the same license.
AGPL-3.0 permits commercial use of unmodified binaries. However, any modifications, derivative distributions, or network-exposed services must publish source code under AGPL-3.0. Organizations building proprietary extensions or offering TDengine as a service component must publish modified code or obtain separate commercial licensing. Requires legal review before use in closed-source products or managed services.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | High |
| DEV.co fit | Good |
| Assessment confidence | High |
Written in C (memory safety not enforced by language); security considerations include buffer overflow, injection, and credential management typical of systems languages. CII Best Practices badge suggests some hardening. Unknown: penetration testing results, vulnerability disclosure policy, encryption-at-rest/in-transit status, authentication/authorization model maturity, and history of security advisories.
Alternatives to consider
InfluxDB
Mature, widely-adopted time-series database with simpler operational model and permissive BSL/commercial licensing; less complex clustering but may have lower ingestion throughput on high-cardinality workloads.
Prometheus + long-term storage (Thanos, Cortex)
Industry-standard open-source monitoring stack with strong Kubernetes integration and mature ecosystem; better for metrics-focused workloads but requires external components for high-volume streaming ingestion.
TimescaleDB (PostgreSQL extension)
Purpose-built time-series on top of PostgreSQL with strong ACID guarantees and relational query support; simpler for workloads requiring cross-entity JOINs and transactional consistency.
Build on TDengine with DEV.co software developers
Review AGPL-3.0 licensing implications, test build and deployment on Linux, and validate cluster failover scenarios. Contact legal if modifications or SaaS integration planned.
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TDengine FAQ
Can I use TDengine in a proprietary product?
What is the difference between TDengine open-source and TDengine Cloud?
Does TDengine support Windows?
What are the minimum system requirements?
Work with a software development agency
DEV.co helps companies turn open-source tools like TDengine into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your open-source databases stack.
Ready to evaluate TDengine?
Review AGPL-3.0 licensing implications, test build and deployment on Linux, and validate cluster failover scenarios. Contact legal if modifications or SaaS integration planned.