Comparison between opensearch and elasticsearch

OpenSearch is an open source search and analysis engine based on Elasticsearch. It has many similarities with Elasticsearch, but there are also some differences:

1. Open source license: OpenSearch uses the Apache License 2.0 open source license, while Elasticsearch uses the Elastic License. Apache License 2.0 is a widely used open source license that allows users to use, modify and distribute OpenSearch freely.

2. Community Governance: OpenSearch is developed and maintained by an independent community organization consisting of some large technology companies and individual contributors. Elasticsearch is developed and maintained by Elastic.

3. Features: OpenSearch is similar to Elasticsearch in basic functions, but OpenSearch also includes some new features, such as data lake support, real-time SQL query, etc.

4. Compatibility: OpenSearch is basically compatible with Elasticsearch's API and index format, but there may be differences in some details.

In general, OpenSearch is a search and analysis engine with openness, flexibility and scalability, and its emergence provides users with more choices and control.

Compare content		opensearch	elasticsearch	Remark
advantage		A variety of Chinese and English word breakers, industry word breakers, all come from the technical achievements of Ali NLP, The effect is significantly better than the open source tokenizer. Built-in a variety of mature advanced algorithm functions, Users can use it through simple interaction on the console, No additional independent research and development is required, and the search effect can be improved with one click. The manual intervention function means that the intervention takes effect.	Open source products are more flexible. For customers with development capabilities, Using es, you can self-develop plug-ins and algorithms that are more suitable for your own business. And the iteration rhythm can be completely controlled by yourself. Data access methods are basically unlimited. Therefore, no matter where the business data is stored, it can be more conveniently accessed to es. Brand soft power, the world-renowned open source search engine.
shortcoming		Compared with es, the data access method is more limited. Currently, only rds and odps on the cloud are supported, or users push via API/SDK. Basically all algorithm functions are black box, Users can't iterate opensearch's algorithm functions according to their business, and the flexibility is not enough; service deployment is currently less	If there are high requirements for search effects, the development difficulty of es is relatively high. For example, OpenSearch supports two rounds of sorting by default, and users can fill in each round of sorting expressions on the console. However, the implementation of the two-round sorting of es has requirements for the rationality of the index configuration. The service needs to be restarted every time the custom word segmentation file is uploaded, which is less convenient.