Apache IoTDB is a high-performance time-series database designed for managing large volumes of data generated by Internet of Things (IoT) devices.
It provides an integrated solution for data collection, storage, querying, and analysis, with a focus on handling high-frequency time-series data efficiently across both edge and cloud environments.
The system uses a columnar storage format optimised for time-series workloads and supports high-throughput data ingestion with low-latency queries. Its architecture is designed to scale from single-node deployments to distributed clusters, making it suitable for industrial IoT scenarios that require reliable, real-time data processing and analytics.
This is free and open source software.
Key Features
- Time-series database designed specifically for IoT data collection, storage, and analysis.
- High-throughput read and write capabilities supporting large numbers of connected devices.
- Columnar storage engine with high compression ratio for efficient disk usage.
- SQL-like query language with rich time-series functions and aggregation support.
- Flexible deployment options including standalone, cluster, edge, and cloud environments.
- Integration with big data and analytics ecosystems such as Hadoop, Spark, and Grafana.
- High availability distributed architecture with automatic load balancing.
Website: github.com/apache/iotdb
Support:
Developer: Apache Software Foundation
License: Apache License 2.0
IoTDB is written in Java. Learn Java with our recommended free books and free tutorials.
Related Software
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|---|---|
| MariaDB ColumnStore | Uses a massively parallel distributed data architecture |
| DuckDB | In-process SQL OLAP database management system |
| Druid | High performance, real-time analytics database |
| Databend | Cloud data warehouse |
| ClickHouse | Real-time analytics database management system |
| InfluxDB Core | Scalable datastore for metrics, events, and real-time analytics |
| Doris | Modern data warehouse for real-time analytics |
| VictoriaMetrics | Scalable solution for monitoring and managing time series data |
| StarRocks | High-performance analytical database |
| MonetDB | High performance relational database system for analytics |
| Kudu | Distributed data storage engine |
| Pinot | Real-time analytics platform |
| CrateDB | Distributed SQL database management |
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