Unified Multi-Database Querying With Native Pagination Mapping
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Solution Overview
Problem
Existing methods for querying multiple databases require users to generate and execute separate queries for different databases, which can be cognitively burdensome and result in a poor user experience due to the need to manage and view separate result sets independently, especially when databases use different technologies and pagination techniques.
Innovation Solution
A search engine that processes a single input search query to identify and query multiple databases, generates individual native queries, combines search results, and uses custom pagination cursors to manage pagination across databases with different techniques, providing a unified search interface and cohesive result display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users query multiple databases separately, then each database can be accessed with its native query language, but the user experience deteriorates due to cognitive burden and separate result set management
Solution Approach 1:
The search engine acts as an intermediary between the user and multiple databases. It receives a single search query, translates it into multiple database-specific queries, executes them against different databases, and combines the results into a unified response. This mediator approach allows users to interact with a single interface while accessing multiple databases with different query languages and pagination techniques.
Solution Approach 2:
The search engine provides a universal interface that can query multiple different databases regardless of their specific technologies or pagination methods. It handles diverse database systems (SQL, NoSQL, document stores, etc.) through a single unified query mechanism, making the system multi-functional and adaptable to various database types without requiring users to learn different query syntaxes.
2Reliability
If separate queries are executed for each database, then database-specific optimization is maintained, but time consumption increases due to multiple independent query executions and result consolidation
Solution Approach 1:
The search engine performs preliminary translation of the user's search query into multiple database-specific queries before execution. It analyzes the query structure, identifies the appropriate databases, generates optimized native queries for each database type, and prepares them for simultaneous execution. This preliminary preparation ensures that when queries are executed, they can proceed efficiently without requiring real-time translation or adaptation during the query process.
3Productivity
If databases use different pagination techniques, then each database can optimize its data retrieval, but system complexity increases due to the need to manage and integrate results from different pagination methods
Solution Approach 1:
The search engine handles different pagination techniques by transforming them into a unified pagination parameter system. It detects the pagination method used by each database (offset-based, cursor-based, keyset-based, etc.) and converts all results to a common pagination format. This parameter transformation allows the system to maintain the efficiency benefits of various pagination methods while presenting a consistent, simplified pagination interface to users.
Solution Approach 2:
The search engine segments the pagination management task by handling each database's pagination independently through its own optimized method, while then integrating the results at the search engine level. Each database query can use its most efficient pagination technique, and the search engine consolidates these segmented results into a unified response, maintaining both database-specific optimization and system-wide simplicity.
Data Source
AI summary
A database querying method is disclosed. The method includes receiving an input search query that defines a first queryable entity, a second queryable entity, and a search clause. The method further includes identifying a first database for first queryable entity, translating the search clause into a first native query executable by the first database, and generating a first set of search results obtained using the first native query. In addition, the method includes identifying a second database for the second queryable entity, translating the search clause into a second native query executable by the second database, and generating a second set of search results obtained using the second native query. The method further includes generating a combined set of results that includes results from the first set and the second set of search results, and communicating the combined set of search results to the client application.