tencent cloud

Data Lake Compute provides agile and efficient data lake analysis and computing services. With its serverless design, it frees you from the concerns over underlying architecture and compute resource maintenance. Its standard SQL syntax enables federated analysis and computing of data stored with COS and other cloud data services. In addition, it eliminates your need to set up traditional data layers, greatly accelerating the preparations for massive data analysis while enhancing your data agility.

Data Lake Compute is a SaaS-like, cloud-native data lake solution that is agile and smart with the following features:

• It provides stable, secure, and high-performance compute resources based on Tencent Cloud's big data kernel enhancement capabilities.
• It implements data processing and multi-source federated data computing by using the standard SQL syntax to greatly reduce your costs to set up and use data analysis services while improving your data agility.
• It offers more economical cost models and accurate cost control capabilities through storage-computing separation and elastic scaling within minutes.
• It delivers SaaS-like out-of-the-box services that eliminate your concerns over the underlying architecture and compute resource maintenance, thereby making it easier for you to get started with data computing.

Features

Agile and real-time data lake analysis

Data Lake Compute leverages a big data analysis architecture with separated storage and computing. It enables fast and flexible deployments based on big data component containerization and implements unlimited expansions on top of cloud object storage. Its advanced cloud-native elastic model fits virtually any type of business to reduce your costs. As a cost-effective and highly elastic cloud data lake solution, it helps you unify data assets and maximize performance for agile and innovative business applications.

Enterprise-grade agile data platform

Data Lake Compute is a new data architecture with closed-loop big data analysis that is lightweight, agile, easy-to-use, and cost-effective. It has a unified metadata management view that allows you to break through data silos. It combines the strengths of many cloud-based big data services to accommodate real-time and offline data analysis scenarios and comprehensively solve a wide range of data problems. Moreover, with convenient and swift data flows, it features many of the capabilities and advantages of different cloud services, making it an ideal option for enterprises setting up a data middleend.

Multi-source federated data lake analysis

Data Lake Compute helps you seamlessly transition from database to big data scenarios, where you can query and analyze multi-source heterogeneous data in the cloud from object storage, database, and other services. Its unified data view and standard SQL capabilities speed up federated data query and analysis, breaking down data silos while fully tapping into the value of data.

Rich and diversified data lake portfolio

A data lake is the foundation for big data in AI scenarios, including machine learning and deep learning. Connected to a wealth of AI capabilities and platforms, Data Lake Compute readily supports a multitude of machine learning capabilities and delivers comprehensive solutions to various smart data lake analysis applications. It opens up multiple industry databases free of charge so that you can perform data analysis without data acquisition and cleansing. It also provides strong BI capabilities to help you gain data insights through predictive analysis.

Product Architecture

• Provides JDBC and SDK development modes and a visually interactive console for various use cases.
• Supports multiple data sources and unifies metadata management and column-level data security management for data consistency and security.
• Supports Spark and Presto engines with unified SQL syntax.
• Caches and accelerates queries for more agile and efficient data query and analysis.
• Integrates COS and Iceberg data storage to ensure the ACID of data transactions.