Overview

Singdata Lakehouse is a cloud lakehouse platform developed by Singdata. Built on an incremental computing engine, it delivers up to 10x better performance than traditional open-source architectures such as Spark, enabling end-to-end, low-cost, real-time processing for large-scale data. The platform supports the integration, storage, and computation of all data types, providing the data infrastructure enterprises need to move from Spark-based systems to AI-ready data platforms.

For enterprises with existing data lakes (S3 / OSS / COS), Singdata Lakehouse can mount existing object storage and query Hive, Iceberg, Delta Lake, and other data formats through External Catalog. This provides high-performance SQL analytics without data migration and offers a low-cost path from a data lake to a unified lakehouse.

Singdata Lakehouse supports seven cloud providers worldwide, is available in multiple Asia-Pacific regions, and also supports private deployment. Deployment costs can be reduced to 1/5-1/3 of traditional solutions, with operations costs close to zero.

Migrate from Spark / Databricks
Migration Guide · Migration Best Practices · SQL Syntax Comparison · Spark Connector · Performance Benchmarks

Accelerate on Existing Data Lake
On-Site Acceleration Implementation Guide · External Catalog Federation Query · External Tables · Object Storage Mount · Performance Benchmarks

AI Data Infrastructure
Lakehouse AI Overview · AI Data Preparation · Vector Search · AI Gateway · Data Analytics Agent · Data Engineering Agent

Cloud Platforms & Deployment
Supported Cloud Platforms and Regions · Pricing and Billing

First Time Here?

①

Create Your Account
5 minutes

Register an account, activate a service instance, and complete initial setup

Get Started →

②

Quick Start Experience
30 minutes

Walk through data ingestion, SQL querying, and Dynamic Table incremental computing

Start Exploring →

③

Go Deeper by Role
On demand

Dedicated paths for data engineers, analysts, AI engineers, and administrators

Choose Your Path →

--- ![](/.topwrite/assets/anim-40-product-architecture.svg) --- ## Who Are You and What Do You Want to Do?

Role / Scenario	Recommended Starting Point
Data Integration / Data Sync Data ingestion, CDC sync, file import, streaming writes	Studio Data Integration (visual configuration for 40+ data sources) · Real-time Sync Tasks (MySQL / PG / Oracle full-database CDC) · Batch Sync Tasks (scheduled batch sync) · Pipe Continuous Ingestion (object storage / Kafka automatic writes) · COPY INTO (one-time file import) · Complete Data Integration Guide
Data Engineer Build data pipelines, process ETL jobs, and manage data warehouse layers	Dynamic Table Incremental Computing · Dynamic Table Overview · Streaming Data Pipeline · Studio Task Development & Scheduling · DDL Syntax Reference · SQL Reference · cz-cli Command Line Tool · Data Engineering Agent · TPC-DS Benchmark
Data Analyst SQL queries, BI connections, ad-hoc analysis	Run Your First SQL Query · Connect BI Tools · Data Analytics Agent (natural language queries) · Semantic Views · SSB Benchmark · TPC-H Benchmark
AI / ML Engineer Vector search, RAG, AI functions, model invocation	AI Data Preparation · Vector Search · AI Functions (AI_COMPLETE / AI_EMBEDDING) · AI Gateway · Python SDK · ZettaPark (DataFrame API)
Platform Administrator User management, permissions, compute clusters, cost control	Account and Service Instance Setup · User and Permission Management · Compute Cluster Management · Pricing and Billing
AI Agent / Automation Deterministic API calls, semantic layer queries, automated data pipelines	cz-cli Command Line Tool (deterministic interface, suitable for Agent calls) · Semantic Views (business semantic layer) · Python SDK · ZettaPark · Data Analytics Agent · Data Engineering Agent · Singclaw

Core Capabilities

Data Integration

40+ data sources are supported out of the box: MySQL / PG / Oracle full-database CDC real-time sync, Kafka streaming writes, S3 / OSS / COS continuous file ingestion, and COPY INTO one-time batch import.

Data Integration Guide · Studio Data Integration · Pipe · COPY INTO

Unified Lakehouse

For existing data lakes (S3 / OSS / COS), no migration is required. Mount existing object storage directly and query Hive, Iceberg, and Delta Lake data through External Catalog to gain high-performance SQL analytics.

External Catalog · External Volume · On-Site Acceleration Guide

Incremental Computing

Define transformation logic in standard SQL. Dynamic Table automatically detects upstream changes and refreshes incrementally, replacing manual scheduling scripts for low-latency data pipelines.

Incremental Computing · Dynamic Table Overview · Streaming Data Pipeline

High-Performance SQL Analytics

A vectorized execution engine supports OLAP multidimensional analysis and ad-hoc queries. On TPC-DS / TPC-H / SSB benchmarks, performance can be up to 10x faster than traditional Spark architectures.

TPC Benchmark Reports · SQL Usage Guide

AI Native

Vector indexes, full-text search, AI functions (AI_COMPLETE / AI_EMBEDDING), and Semantic Views are built into the data platform. Build RAG knowledge bases and AI-enhanced analytics without external services. Data Analytics Agent supports conversational data queries in natural language; Data Engineering Agent supports ETL development in natural language.

Lakehouse AI Overview · Vector Search · AI Functions · Semantic Views · Data Analytics Agent · Data Engineering Agent

Studio & AI Agent Integration

Built-in IDE, task scheduling, data integration, data quality, and operations monitoring provide a unified data development platform. cz-cli provides a deterministic command interface, and Semantic Views provide a business semantic layer so AI Agents can call data capabilities directly.

Studio User Manual · cz-cli Installation and Usage · Semantic Views

What's New

→ Product Updates

In This Section

Page	Description
Before You Begin	Ways to access Lakehouse: Studio, CLI, drivers and connectors
Account Signup and Setup	Register an account, activate a service instance, and complete initialization
Cloud Services and Regions	Supported cloud providers and available regions
Trial Account Quotas and Limits	Resource quotas during the trial period