Top 10 Database Management Systems for IoT Applications in 2027

Apache IoTDB is an industrial IoT time-series database management system for integrated collection, storage, management and analysis of IoT time-series data. It has a lightweight architecture with edge-cloud collaboration, and IoTDB Edge runs the ConfigNode and DataNode in one JVM for resource-constrained, single-node deployments. Data is stored in TsFile, a columnar format designed for time series. It uses a SQL-like language and JDBC, integrates with Hadoop, Spark, Flink and Grafana, is Apache-2.0 licensed, and has 6,429 GitHub stars. The image is an IoTDB architecture diagram of a station-to-regional-center deployment.

TDengine connects to OPC, MQTT, Kafka and other industrial data sources with built-in ETL, and runs on public cloud, on premises or edge-cloud. It is free forever for up to 5,000 tags, and paid quotes depend on tag count, sites, deployment model and support. TDengine lists manufacturing, renewables, utilities, and oil and gas use cases, and Nevados scaled from 4,000 to 34,000 trackers for a 1 GW solar fleet. The open-source edition is listed under AGPL-3.0 on GitHub, with 25,187 stars. The image shows a TDengine cluster dashboard.

InfluxDB 3 Core is positioned for edge computing, IoT prototypes and single-node production workloads, and can run on edge devices, on-premises servers, private clouds or hybrid setups. InfluxData claims sub-10 millisecond queries for live and recent data, a Python processing engine inside Core, and SQL and InfluxQL support. Core has no usage fees and is licensed under MIT and Apache 2.0; Enterprise trials run 30 days by default. The repository has 31,802 GitHub stars. The image shows the InfluxDB 3 Data Explorer query screen.

TimescaleDB turns any Postgres table into a hypertable partitioned automatically by time or id, compresses data by up to 95% (a vendor claim), and refreshes continuous aggregates incrementally, with about 200 native SQL functions. Tiger Cloud Performance starts at $30/month and Scale at $36/month, with a 30-day free trial and no credit card. The repository has 23,825 GitHub stars. The image shows the Tiger Cloud monitoring view.

CrateDB says it ingests millions of events per second from sensors, telemetry streams, Kafka or application logs, with data queryable immediately. It uses standard SQL, joins device metadata at query time without ETL, and runs on-prem, at the edge, in any cloud or as a managed service under Apache 2.0. ABB reports 1 million values ingested per second and TGW Logistics 900,000 sensors per distribution center, as quoted by CrateDB. There is a free cloud plan, and Dedicated starts at $0.246 per hour. The image is the CrateDB Admin UI cluster view.

Azure Data Explorer is described as useful for log analytics, time series analytics, IoT and general-purpose exploratory analytics. It ingests at a velocity of millions of events per second with latency of seconds, and provides time series functions for regression, seasonality detection, anomaly detection and forecasting, optimized for thousands of time series in seconds. It uses Kusto Query Language and also supports T-SQL. Billing is per minute per VM plus a markup, and the markup is not charged on Developer tier clusters. The image is a column chart in the Azure Data Explorer web UI.

Google Cloud Bigtable lists time-series data and Internet of Things data, such as readings from energy meters and home appliances, among its use cases. It is a sparsely populated table that can scale to billions of rows and thousands of columns, scales in proportion to the number of machines in the cluster, and replicates automatically when you add a second cluster. The Enterprise edition default list price is $0.65 per node per hour. The image is the Bigtable architecture diagram.

MongoDB lists IoT first among time series collections use cases, with sensor data such as smart home devices or fleet logistics. Time series collections use a columnar storage format in time order, which reduces disk usage and read I/O, and MongoDB 6.3 and later creates a compound index on the time and metadata fields automatically. They were new in version 5.0. Atlas has a free M0 tier with 512 MB, Flex from $0.011 per hour capped at $30/month, and Dedicated from $0.08 per hour. The image is an Atlas Charts sample dashboard.

Redis TimeSeries lists Internet of Things (IoT) sensor data and smart metering among its use cases. TS.ADD appends a sample, TS.MADD adds samples to several series in one call, each series can have a retention period and labels, and compaction rules aggregate data into a destination series. Redis Cloud has a free plan up to 30 MB, Essentials from $0.007 per hour ($5/month) and Pro from $0.014 per hour with a $200/month minimum. The redis/redis repository has 77,287 GitHub stars. The image is the Redis Insight time series chart view.

Couchbase Lite is an embedded NoSQL JSON document database designed for mobile and edge devices. It works without a constant internet connection, offers bi-directional sync with cloud and edge through Sync Gateway, supports peer-to-peer sync between devices, and queries with SQL++ plus vector search. Pricing is not published on the documentation page. It is not a time-series database, so it suits offline-first device apps rather than sensor analytics. The image is the Couchbase Lite and Sync Gateway architecture diagram.