Day 30: OpenSearch

𝐎𝐩𝐞𝐧𝐒𝐞𝐚𝐫𝐜𝐡:

👉 You can search any field, even partially matches.

👉 Does not natively support SQL (can be enabled via a plugin)

👉 It’s common to use OpenSearch as a complement to another database

OpenSearch:

Key Features:

1. Search Functionality:

• OpenSearch is a search and analytics engine that allows users to search, analyze, and visualize large volumes of data in real-time.
• It supports searching across various fields, even for partial matches, making it versatile for different use cases.

2.SQL Support:

• OpenSearch does not natively support SQL queries. However, SQL support can be enabled through a plugin, allowing users to query the data using SQL syntax.

3.Complementary Database:

• It’s common to use OpenSearch in conjunction with another database. This could mean using OpenSearch for specific search and analytics tasks while relying on another database for transactional or storage purposes.

👉 Search Functionality:

1. Real-time Search and Analytics:

• OpenSearch is designed to provide real-time search capabilities, enabling users to search and analyze large volumes of data as it is ingested.
• The engine is optimized for quick and efficient searches, making it suitable for applications where real-time insights are crucial.

2.Versatility in Field Searching:

• One of the strengths of OpenSearch is its ability to search across various fields within the indexed data.
• The engine supports complex queries, allowing users to specify search criteria based on different fields, and it can handle partial matches, making it adaptable to a wide range of use cases.

3.Scalability:

• OpenSearch is designed to scale horizontally, meaning it can handle growing amounts of data and search queries by adding more nodes to the cluster. This scalability makes it suitable for applications with increasing data volumes.

👉 SQL Support:

1. Native and Plugin-based SQL:

• OpenSearch, by default, does not natively support SQL queries. However, it provides the flexibility to enable SQL support through plugins.
• The SQL plugin allows users to query the data using SQL syntax, providing a familiar and powerful interface for those who are accustomed to relational database querying.

2. Enhanced Query Capabilities:

• SQL support in OpenSearch enhances its query capabilities, enabling users to perform more complex data manipulations and analysis using standard SQL commands.

👉 Complementary Database:

1. Specialized Search and Analytics:

• OpenSearch is often used in conjunction with another database that may serve as the primary data store. OpenSearch is then employed for specialized tasks related to search and analytics.

2.Separation of Concerns:

• By using OpenSearch as a complementary database, organizations can benefit from a separation of concerns. The primary database can focus on transactional or storage-related tasks, while OpenSearch can handle tasks related to searching, analyzing, and visualizing the data.

3.Optimized for Specific Workloads:

• OpenSearch’s strengths lie in its search and analytics capabilities. Leveraging it alongside another database allows organizations to use the right tool for the right job, optimizing performance and resource usage for specific workloads.

4.Elasticsearch Ecosystem Integration:

• OpenSearch is part of the Elasticsearch ecosystem, which includes tools like Kibana for data visualization and analysis. Integration with this ecosystem enhances the capabilities of OpenSearch for comprehensive data management and insights.

Reference Links:

https://www.linkedin.com/pulse/transform-your-search-experience-aws-opensearch-ultimate-huzaifa-asif/

https://coralogix.com/blog/4-ways-ingest-data-aws-opensearch/