# Singdata Lakehouse Introduction

Singdata Lakehouse is a fully managed data management and analysis service based on the open lakehouse architecture. Singdata Lakehouse meets the needs of data warehouse construction, data lake exploration and analysis, batch/real-time data processing and analysis, business reports, etc., all these workloads with a single engine. It meets the needs of scalability, cost, and performance at different stages of the enterprise through compute-storage separation architecture, Serverless elastic computing power, and intelligent optimization features. Built-in data integration, development and operation, data asset management and other services are available upon activation, greatly simplifying data development and management work, and accelerating enterprise data insight and value realization.
![](.topwrite/assets/image_1710684652463.png)

## Core  Features

We are committed to meeting the management requirements of enterprise-level users, while continuously improving the platform's ease of use, flexibility, and openness to achieve the best user experience.

![](.topwrite/assets/image_1710684668475.png)

## Key  Features

### Next-Generation SQL Data Processing Engine

A single engine meets the needs of batch, stream, and analysis scenarios, without the need for multiple component combinations. With a single engine, it simultaneously meets the needs of batch processing, real-time computing, and online analysis scenarios, effectively reducing the threshold for data application development and accelerating value delivery. High performance across all scenarios, cloud-native, compute-storage separation architecture, vectorized execution engine. Under the same resource scale, it leads the mainstream products in the industry on the TPCDS10TB/TPCH100GB/SSB 100GB test set.

![](.topwrite/assets/image_1710684703287.png)

### Serverless Elastic Architecture

The compute-storage separation virtual computing cluster design optimizes calculations for ETL and analysis scenarios using different execution engines. It supports the creation of virtual clusters needed for different business needs on demand, isolating the impact between businesses while meeting different needs for high throughput and high performance. It senses business load, automatically manages the start and stop of the cluster and second-level elastic concurrency, while meeting the needs of low cost and high SLA.

![](.topwrite/assets/image_1710684714663.png)

### Open, No Lock-in

The storage layer is compatible with mainstream open storage formats, and the metadata service provides open metadata services in the form of Catalog. After external engines authenticate and authorize the user's identity, they can access the data files of Singdata Lakehouse. On the basis of a unified security policy, it provides the best openness, releases greater data value with the help of a rich open-source ecosystem.

![](.topwrite/assets/image_1710684730323.png)

### Unified Data Assets

Supports structured data in the form of Tables, and unstructured data in the form of files and directories for unified storage, and provides fine-grained access control based on ACL. It realizes the assetization and secure access control of various structured data. Different sources and types of data are unified into a centralized storage repository to achieve excellent performance, simplicity, and consistency. Supports unstructured data exploration and analysis.
![](.topwrite/assets/image_1691805420547.png)

### Integrated Solution for Data Development and Management

The engine capabilities and platform tools are seamlessly integrated to meet the needs of data integration, development and operation, data catalog, security governance, data analysis and system management under a unified Web user experience. With the help of storage-computing separation, on-demand elastic virtual clusters, and automated operation and maintenance and optimization features, it shields the need for infrastructure operation and maintenance management, providing an integrated data platform solution with a SaaS-like development management experience.

![](.topwrite/assets/image_1710684752427.png)

## Typical Use Cases

### Upgrading Traditional Solutions with an Integrated Data Platform

![](.topwrite/assets/image_1710684770709.png)

### IoT Data Analysis Scenarios

![](.topwrite/assets/image_1710684779746.png)

### Customer-Oriented Data Applications

![](.topwrite/assets/image_1710684790045.png)
