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IoT Analysis
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Real-Time Data Processing
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Real-Time File Transfer
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Data Intake and Backup
IoT Analysis and Applications
IoT ingestion components can quickly collect IoT device data with multiple IoT protocols, such as MQTT, CoAP, STOMP, and LwM2M, to implement upstream data transmission. They can also receive messages from other services on the cloud, convert the messages into IoT messages, and push the messages to the client to implement downstream data transmission.
Advantages
Multi-Protocol Support
With support for MQTT, CoAP, STOMP, and LwM2M protocols, IoT ingestion components can quickly interconnect with different systems and support upstream and downstream data transmission.
Rock-Solid Reliability
Multiple authentication mechanisms are provided and TLS transmission encryption is supported.
Elastic Scaling
DIS employs the distributed architecture for elastic expansion to quickly response to business changes.
Real-Time Data Processing
DIS collects real-time vehicle traffic data and caches the data in DIS streams. The data is analyzed to facilitate traffic control.
Advantages
Real-Time
DIS receives data from application systems in real time.
High Concurrency and Low Latency
Millions of messages can be concurrently processed with an E2E millisecond-level latency.
Openness
DIS can work with various analysis platforms to provide one-stop data transmission and computing.
Real-Time File Transfer
DIS collects files from application systems in real time, uploads them to the cloud, and identifies VIP customers and potential customer needs through analysis and machine learning.
Advantages
Automatic Collection of Incremental Data
Incremental data or new files can be automatically collected.
Easy to Use
DIS provides agents for different platforms to simplify data collection.
High Security
HTTPS-encrypted transmission ensures data security.
Data Intake and Backup
DIS backs up a lot of log files to the cloud for data recovery or exception analysis. Small log files can be merged and dumped into a single large file to accelerate data processing.
Advantages
Multiple Data Sources
DIS supports open source systems such as Kafka and Flume and therefore can easily integrate with other systems.
Efficient Data Transmission
You can scale the DIS stream capacity based on the volume of input data.
Massive Small File Transfer
Small files are migrated to the cloud and then dumped to OBS.
Related Services
obs
Functions
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IoT Data Ingestion
Multiple IoT protocols are supported, enabling quick IoT data ingestion.
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Data Collection
DIS provides RESTful APIs, SDKs, and agents to collect offline data from various sources in real time.
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Data Transmission
DIS transmits data in real time with high concurrency, high reliability, and low latency.
IoT protocols including MQTT, CoAP, STOMP, and LwM2M are supported.
Bidirectional transmission of IoT data is supported.
Multiple data sources
DIS collects data from user application systems, Kafka systems, and Flume systems in real time.
Multiple data intake modes
DIS provides RESTful APIs, SDKs, and agents for real-time data intake with minimum configuration required.
DIS supports millions of concurrent connections. Each DIS stream can ingest terabytes of data per day, and each partition supports data write speeds of up to hundreds of gigabytes per day.
The throughput of each DIS stream can scale dynamically by adding partitions.
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Data Movement
DIS provides multiple connectors to move data freely between storage, computing, and analysis services.
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Data Processing
DIS comes preloaded with the connectors to extract, aggregate, convert, and preprocess data input from users.
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Data Caching
DIS preserves real-time data for up to 7 days depending on configurations, ensuring data security.
DIS is integrated with the OBS, MRS, DWS, CloudTable, DLI, CS, and FunctionGraph to simplify data dumping, computing, and analysis.
Data can be imported to cloud services such as CloudTable, DWS, HBASE, RDS, and DCS by simply configuring the agents between DIS and these cloud services.
DIS converts data from CSV/JSON format to Parquet/CarbonData format, improving user data quality.
