IoT Database that truly Scales
In the world of Internet of Things, managing the volume, variety, and speed of data collected is a constant challenge. With its fast data ingestion, versatile data modeling, and real-time querying capabilities, CrateDB helps businesses harness the full value of high-volume data from thousands of sensors.
Traditional IoT database systems frequently struggle to keep up with the massive volumes of data generated by thousands of sensors. CrateDB overcomes this challenge by providing fast, scalable data ingestion, processing millions of IoT data points per second, while indexing and making data available for query in real-time. This enables businesses to achieve real-time monitoring, improved operational efficiency, and faster decision-making.
High performance
- Data is available for query instantly after data ingestion
- Response-time in milliseconds - even for complex ad-hoc queries across billions of records - thanks to a fully distributed query engine
- Data aggregations on the fly thanks to columnar storage

Easy scaling

Time-series

Versatile data model

Dynamic schema

Fault tolerance built-in

Easy and seamless integrations
CratDB offers a seamless integration process with popular IoT stack software such as Kafka, Grafana, Node-RED, and more.

Hybrid Edge Deployment
IoT projects often require deployment at the Edge and in the cloud to enable real-time decision-making and analytics in various connectivity scenarios. CrateDB effectively addresses this need by offering versatile deployment options, supporting both on-prem, Edge, and cloud environments.

Interested?
Examples of IoT queries
/* Based on IoT devices reports, this query returns the voltage variation over time
for a given meter_id */
WITH avg_voltage_all AS (
SELECT meter_id,
avg("Voltage") AS avg_voltage,
date_bin('1 hour'::INTERVAL, ts, 0) AS time
FROM iot.power_consumption
WHERE meter_id = '840072572S'
GROUP BY 1, 3
ORDER BY 3
)
SELECT time,
(avg_voltage - lag(avg_voltage) over (PARTITION BY meter_id ORDER BY time)) AS var_voltage
FROM avg_voltage_all
LIMIT 10;
+---------------+-----------------------+
| time | var_voltage |
+---------------+-----------------------+
| 1166338800000 | NULL |
| 1166479200000 | -2.30999755859375 |
| 1166529600000 | 4.17999267578125 |
| 1166576400000 | -0.3699951171875 |
| 1166734800000 | -3.7100067138671875 |
| 1166785200000 | -1.5399932861328125 |
| 1166893200000 | -3.839996337890625 |
| 1166997600000 | 9.25 |
| 1167044400000 | 0.4499969482421875 |
| 1167174000000 | 3.220001220703125 |
+---------------+-----------------------+
/* Based on IoT devices reports, this query returns the voltage corresponding to
the maximum global active power for each meter_id */
SELECT meter_id,
max_by("Voltage", "Global_active_power") AS voltage_max_global_power
FROM iot.power_consumption
GROUP BY 1
ORDER BY 2 DESC
LIMIT 10;
+------------+--------------------------+
| meter_id | voltage_max_global_power |
+------------+--------------------------+
| 840070437W | 246.77 |
| 840073628P | 246.69 |
| 840074265G | 246.54 |
| 840070238E | 246.35 |
| 840070335K | 246.34 |
| 840075190M | 245.15 |
| 840072876X | 244.81 |
| 840070636M | 242.98 |
| 84007B113A | 242.93 |
| 840073250D | 242.28 |
+------------+--------------------------+
/* Based on IoT devices reports, this query returns the voltage corresponding to
the maximum global active power for each meter_id */
SELECT meter_id,
MAX_BY("Voltage", "Global_active_power") AS voltage_max_global_power
FROM iot.power_consumption
GROUP BY 1
LIMIT 10;
+------------+--------------------------+
| meter_id | voltage_max_global_power |
+------------+--------------------------+
| 840073190N | 233.57 |
| 840072401F | 233.53 |
| 840072655G | 234.1 |
| 840071893D | 234.47 |
| 840073950P | 231.73 |
| 840075260N | 235.51 |
| 840076398A | 234.56 |
| 84007B071E | 231.94 |
| 840075959Y | 237.21 |
| 840072534A | 231.96 |
+------------+--------------------------+


"With CrateDB, we can continue designing products that add value to our customers. We will continue to rely on CrateDB when we need a database that offers great scalability, reliability and speed."
Nixon Monge Calle
Head of IT Development and Projects
SPGo! Business Intelligence


"Thanks to CrateDB's great indexing, dedicated data types, and subsequent great performance, we could execute an event and data-driven architecture, with the performance and scalability necessary for storing time-series data over time. The SQL query syntax capability of CrateDB also played a part in achieving this great outcome, as it made it easy for the team to write good performing queries using existing know-how. CrateDB is now an integral part of our big data streaming architecture and it is delivering as promised."
Kristoffer Axelsson
Principal Solution Architect
Thomas Concrete Group


"CrateDB's unmatched concurrency capabilities and simple scaling made it the best solution for us. We tried other solutions, including MongoDB, but it was difficult and expensive to scale for our needs. Plus, CrateDB is SQL, which 90 percent of today's developers know well, and that makes hiring new developers easier."
Waseem Javid Nasiri
Senior developer
Roomonitor



CEO
ALPLA
Want to know more?
Other Industrial IoT resources
White Paper
Industrial IoT in 2023 and beyond
White Paper
Data and industrial IoT
Webinar
IIoT technology. How SPGo! builds apps for monitoring and predictive maintenance
Webinar
How to improve supply chain management with loT data
Webinar
Why IIoT needs its own database?
Product documentation
Logical replication setup between CrateDB clusters
Blog
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