Unified SQL Engine (CyberSQL)

A single SQL surface across sources with federated and cross-database queries, loose coupling to engines, dynamic switching, HA, low latency, and scale for large analytic workloads.

Product Advantages

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Low Latency Response

Support near real-time interaction analysis through in-memory execution of queries and efficient vectorization execution engines.

Simple and Easy to Use

Provides a unified query paradigm that masks the underlying details, allowing users to conduct complex data queries and analyses using the familiar SQL language.

High Scalability

The deployment program is decoupled from the specific version of the data engine to achieve cross-platform and cross-engine flexible migration capabilities of the product program.

Core Capabilities

Multi-Engine Federation Query

Through the unified SQL query engine, the complexity of the underlying heterogeneous data sources is shielded. Users do not need to care about the physical location and storage format of the data, and use standard SQL statements to access a variety of data sources, including relational databases, NoSQL databases, and data lakes, to achieve cross-source joint query of data, greatly improving the flexibility and efficiency of data processing, and meeting the diversified needs of enterprises in complex data ecosystems.

Query Acceleration

Accelerating queries through caching, precomputation, and materialized views can significantly improve query performance. The materialized view precomputes and stores frequently executed query results to retrieve data directly from the materialized view when needed, avoiding access to underlying tables and reducing I/O operations. And allows users to push aggregation, filtering, projection and other operations down to the data engine to achieve millisecond response.

Custom SQL Dialect

Developers can flexibly extend SQL construction and compilation rules as needed to generate more efficient SQL syntax for that particular database to better fit the actual scenario.

Core Capabilities

Through the unified SQL query engine, the complexity of the underlying heterogeneous data sources is shielded. Users do not need to care about the physical location and storage format of the data, and use standard SQL statements to access a variety of data sources, including relational databases, NoSQL databases, and data lakes, to achieve cross-source joint query of data, greatly improving the flexibility and efficiency of data processing, and meeting the diversified needs of enterprises in complex data ecosystems.

Application Scenarios

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Multi-Datacenter, Multi-Source Heterogeneous Data Federation

Business Pain Points

Data is scattered and stored on multiple storage media, and data from different media needs to be extracted and merged when data is produced.

There are grammatical differences in a variety of engines, which require different syntaxes for data processing, and the technical threshold for personnel is high.

Business Value

Based on unified engine technology and unified metadata system, it supports cross-engine federal query engines to open up data for customers in the data center and realize converged computing and analysis of decentralized data in a cost-effective manner. Improve analytics efficiency by reducing unnecessary data transfers and ETL.