Engine kernel
The following table describes the engine-related capabilities of Elasticsearch.
Category | Feature | Description | References |
Query and analysis | Optimization of concurrent asynchronous queries | Concurrent threads are used to return results for queries. This reduces the period of time required to return results for queries. | |
Time series data | Data query by using Prometheus Querying Language (PromQL) statements | The aliyun-timestream plug-in allows you to execute PromQL statements to query data stored in Elasticsearch and is compatible with Prometheus and Grafana. | |
Downsampling | The aliyun-timestream plug-in enables automatic data write and query downsampling, which is imperceptible to users. | ||
AliES enhancement | Self-developed kernel enhancement | A variety of cloud-specific features are provided as plug-ins in terms of performance enhancement, stability improvement, and multi-scenario feature optimization. You can install and configure the plug-ins based on your business requirements. | |
Support for open source capabilities and compatibility of the open source ecosystem | X-Pack advanced features | Alibaba Cloud Elasticsearch cooperates with Elastic and provides the X-Pack commercial plug-in free of charge. X-Pack advanced features provided in the open source Elasticsearch Platinum edition are developed by the open source Elasticsearch team based on the X-Pack plug-in. The features include security, SQL plug-in, machine learning, alerting, and monitoring. These features enhance the service capabilities of open source Elasticsearch in terms of scenario-based artificial intelligence (AI), application development, and O&M management. | |
Support for Elasticsearch Relevance Engine™ (ESRE™) | Alibaba Cloud Elasticsearch supports ESRE™ to provide an AI-enhanced search engine for users in the cloud. ESRE™ integrates AI-related best practices and the powerful search capabilities of Elastic to provide a complete set of mature search algorithms for developers. ESRE™ also integrates large language models (LLMs). | - |
Management platform
The following table describes the platform management-related capabilities of Elasticsearch.
Category | Feature | Description | References |
Network | Public and private network access whitelists | You can use IP addresses, CIDR blocks, or security groups to configure public and private network access whitelists for Elasticsearch clusters and Kibana. | |
HTTPS | You can enable HTTPS to ensure data transmission security. | ||
VPC-based deployment | Clusters are deployed in the virtual private cloud (VPC) within the service account of Elasticsearch. This VPC is connected to your VPCs. This ensures high security. | ||
Cluster management and resource orchestration | Flexible configuration change | Cluster configurations can be flexibly changed based on business scenarios. You can manage cluster plug-ins, add or remove nodes, change node specifications, and resize disks. | |
O&M and monitoring | Cluster monitoring and alerting | A variety of metrics are provided to monitor clusters, and you can configure alerts for clusters based on the metrics. | |
Log query | The following types of logs are provided for clusters: cluster logs, slow logs, garbage collection (GC) logs, access logs, and audit logs. You can query logs based on your requirements. | ||
Event center | You can view O&M events that are triggered by the system and trace and handle the events. | - | |
Disaster recovery | Cross-zone deployment | You can deploy a cluster in a single zone or across two or three zones. Cross-zone deployment can improve the disaster recovery capabilities of a cluster. | |
Data backup | You can create automatic snapshots and restore data from automatic snapshot, create manual snapshots and restore data from manual snapshots, and configure shared Object Storage Service (OSS) repositories to ensure the reliability of data in your cluster. | ||
Cross-cluster replication | You can use the cross-cluster replication (CCR) feature to implement cross-region or cross-cluster data replication. | ||
Security authentication | Lightweight Directory Access Protocol (LDAP) authentication | You can configure LDAP authentication for your Elasticsearch cluster. | |
Active Directory (AD) user authentication | You can configure AD user authentication for your Elasticsearch cluster. | ||
User permission management | You can grant permissions on clusters, indexes, fields, and specific operations to custom roles based on the role-based access control (RBAC) mechanism. | Use the RBAC mechanism provided by Elasticsearch X-Pack to implement access control |
Ecosystem tools
The following table describes the ecosystem tool-related capabilities of Elasticsearch.
Category | Feature | Description | References |
Visualization | Kibana | Elasticsearch clusters support Kibana nodes for cluster data query and visualization. | |
Data processing | Logstash | All open source Logstash capabilities are supported. |