Elasticsearch:Features of the AliES Kernel-enhanced Edition

Enhanced feature category

Feature name

Feature description

Version 7.16

Version 7.10

Version 6.7

Performance enhancement

Analyticsearch retrieval and analysis

Enhances query performance in log scenarios, accelerates Kibana Discover queries, and supports concurrent queries to significantly reduce query time.

For more information, see Use the analytic-search plugin.

×

Supported in kernel versions 1.7.0 and later

×

Physical replication plugin

Provides an index-level configuration switch to enable real-time incremental synchronization between primary and replica shards. This reduces cluster CPU overhead and improves write performance by 60%.

For more information, see Use the physical replication feature of the apack plugin.

×

√

Supported in kernel versions 1.2.0 and later

Bulk write aggregation plugin

Aggregates bulk write requests in batches based on a specified request size and time interval. This improves cluster write throughput by 20%.

For more information, see Use the bulk aggregation plugin (faster-bulk).

√

√

√

Time series query pruning

In time series scenarios, queries crop data based on a time range. This improves the query performance of ranges that contain time series fields by 30%.

For more information, see Use the time series query pruning feature.

√

√

√

Stability improvement

QoS throttling plugin

Implements index-level read and write throttling for a cluster. It degrades indexes based on specified rules to control read and write traffic and improve stability.

For more information, see Use the cluster throttling plugin (aliyun-qos).

√

√

√

Cost optimization

Index compression plugin

Supports multiple compression algorithms such as Brotli and Zstd to compress index files. This reduces the storage size of indexes by more than 40%.

For more information, see:

Versions 7.16 and 7.10: Use the aliyun-codec plugin

Version 6.7 (supported only for instances created before April 2024): Use the index compression plugin (beta) (codec-compression)

√

√

√

Feature optimization

Timestream plugin

Supports the creation, retrieval, update, and deletion of time series indexes. It also supports downsample writes and Prometheus Query Language (PromQL) queries. This significantly reduces time series storage and usage costs.

For more information, see Introduction to the TimeStream time series enhancement engine.

Supported in kernel versions 1.8.0 and later

Supported in kernel versions 1.7.0 and later

×

Aliws tokenizer plugin

Integrates analyzers and tokenizers that use the NLP technology of Alibaba DAMO Academy. It provides a more comprehensive tokenizer library for data retrieval and analysis.

For more information, see Use the AliNLP tokenizer plugin (analysis-aliws).

√

√

√

Feature name

Feature description

Billing description

Indexing Service

Suitable for scenarios such as log retrieval and time series metric analysis that have high write TPS, large fluctuations in write traffic, and low query QPS.

• Based on a read/write splitting architecture, it forwards data writes to a cloud service for index building. This offloads write pressure from your cluster.

• Cloud-based write resources automatically scale to match resources with traffic. This provides more than 10 times the write elasticity to handle traffic fluctuations and peak write bottlenecks.

• You are charged for writes based on actual traffic. You do not need to reserve resources for peak writes, and no resources are idle during off-peak hours. In high-write scenarios, cluster compute resource costs can be reduced by more than 50%.

For more information, see Introduction to Indexing Service.

You are charged for the actual write traffic.

Openstore intelligent hybrid storage

Suitable for scenarios such as log retrieval, metric analysis, and data archiving that require long-term storage of massive data, have low query QPS, and can tolerate relatively high query latency.

• Based on a compute-storage separation architecture, you do not need to plan or purchase cluster data storage space in advance. You are charged on a pay-as-you-go basis for the actual storage data size. The unit price for storage is 70% lower than that of cloud disks, which significantly reduces cluster storage costs.

• It goes beyond traditional hot and cold data separation architectures. It automatically performs intelligent tiering based on query frequency. You do not need to configure index lifecycles for hybrid storage.

• Multiple replicas share one copy of data without increasing storage costs. This provides 12 nines of data high availability.

For more information, see OpenStore intelligent hybrid storage (for log analysis) engine.

You are charged for the actual Openstore storage space.