aliyun-timestream is a plug-in for Alibaba Cloud Elasticsearch that adds native time series data management to Elasticsearch. It replaces complex DSL queries with Prometheus Query Language (PromQL) and cuts storage costs by more than 80% compared with standard Elasticsearch indexes.
Use cases
aliyun-timestream is suited for the following scenarios:
Storing and querying system metrics and IoT device data
Using Prometheus and Grafana against an Elasticsearch backend
Reducing storage costs for large-scale time series workloads
Cluster requirements
To use aliyun-timestream, your Elasticsearch cluster must meet one of the following version requirements.
| Cluster version and kernel version | Region |
|---|---|
| Elasticsearch V7.16 or later + kernel V1.7.0 or later | China (Shenzhen), China (Chengdu), China (Guangzhou), China (Ulanqab), China North 2 Finance, and China (Hong Kong) |
| Elasticsearch V7.10 or later + kernel V1.8.0 or later | China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), and China (Zhangjiakou) |
Supported regions may change. Check the Elasticsearch console for the current list.
Key capabilities
Simplified time series data management
aliyun-timestream provides APIs to create, modify, query, and delete time series indexes. When you create a time series index, the plug-in automatically applies Elasticsearch best practices for time series scenarios—no manual mapping or routing configuration required.
PromQL support and Prometheus integration
aliyun-timestream lets you query Elasticsearch data using PromQL instead of DSL. This enables direct integration with Prometheus and Grafana, reducing operational complexity for teams already in the Prometheus ecosystem. The plug-in also supports downsampling and time-based partitioning for data streams.
Reduced storage costs
aliyun-timestream optimizes data compression and metadata storage, reducing storage requirements by more than 80% compared with standard Elasticsearch indexes for the same data.
Improved read and write performance
Write throughput: Write TPS improves by approximately 40% compared with standard Elasticsearch indexes.
Query and analysis performance: Query and analysis speed improves by 5 times compared with open source Elasticsearch.
How aliyun-timestream compares with standard Elasticsearch
| Dimension | With aliyun-timestream | Without aliyun-timestream |
|---|---|---|
| Data model | Native time series data model | Requires manual configuration: time series ID fields, time-based sort settings, and shard routing |
| Storage | Auto-applied best practices cut storage by 80%+ | Relational data model requires 25 times more storage than the time series model |
| Query language | PromQL; integrates directly with Prometheus and Grafana | Complex DSL statements |