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Data Lake Compute

Tencent Cloud Data Lake Compute provides agile and efficient data lake analysis and computing services to greatly reduce your costs to set up and use data analysis services while improving your data agility.

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Data Lake Compute
Overview
Benefits
Scenarios
Pricing
Help and Documentation

Overview

Overview

Benefits

Scenarios

Pricing

Help and Documentation

Overview

Data Lake Compute is seamlessly integrated into Tencent Cloud's data ecosystem for direct access to data stored in COS. It is compatible with numerous platforms and supports a diversity of upper-layer data applications.

Documentation
Benefits
Pay-as-You-Go Billing
Pay-as-You-Go Billing
Data Lake Compute is billed by scanned data volume or resource usage, greatly reducing your costs to query and analyze data in data lakes. If data partitioning or columnar compression is adopted, the performance can be improved at even lower costs.
Multi-Source Federated Query
Multi-Source Federated Query
Data Lake Compute supports Tencent's many types of cloud-based data infrastructures such as object storage, database, and data warehouse. This implements multi-source federated analysis through a unified data view with no need to load additional data.
Standard SQL Support
Standard SQL Support
With the out-of-the-box and easy-to-use Data Lake Compute, you can analyze your data with standard SQL statements, eliminating the need to understand data structures in different infrastructures or learn new programming languages.
Excellent Resource Elasticity
Excellent Resource Elasticity
Data Lake Compute is serverless, so you don't need to worry about the underlying Ops. The system terminates computing resources after use and scales instantly and dynamically as computing power requirements change.
Seamless Integration in the Cloud
Seamless Integration in the Cloud
Data Lake Compute is seamlessly integrated into Tencent Cloud's data ecosystem for direct access to data stored in COS. It is compatible with numerous platforms and supports a diversity of upper-layer data applications.
High Security and Reliability
High Security and Reliability
Data Lake Compute adopts Tencent Cloud's mature VPC network isolation technology to ensure that tenants are isolated at both the network and resource levels. It further achieves high data reliability and security thanks to Tencent Cloud's superior security hardening.
Scenarios

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.


Typical Use Cases

Batch Log Query

Unlike the typical practice of storing enterprise log data as JSON and text files, you can store data in COS and then use standard SQL statements through Data Lake Compute to batch query and analyze massive amounts of data, with data reports generated quickly. In this way, Data Lake Compute visualizes your data and boosts your productivity. With a few simple configurations, you can also import cloud-based log service data into a data lake for agile analysis.


Service Benefits

  • Cost-effective: Data Lake Compute is pay-as-you-go, allowing you to precisely control costs through its cloud-native data lake architecture with separated storage and computing.
  • Easy-to-use: You can easily get started with Data Lake Compute for faster queries through the unified SQL syntax.
Agile and Real-Time Data Lake Analysis

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.

Typical Use Cases

  • Unified Metadata View

Data Lake Compute enables you to unify all of your different metadata views into one. In this way, you can manage and use metadata from different sources in a centralized manner, build your metadata center with agility, and switch between products and versions seamlessly. Specifically, you can easily reuse the same metadata across products.

  • Agile and Versatile Data Analysis

In the big data ecosystem, Presto excels in performing interactive analysis while Spark does well in ETL tasks. Data Lake Compute provides unified syntax and lightweight clustering capabilities, so the same data can go seamlessly between engines in different scenarios. It also works with WeData so data can be imported from and exported to dozens of products and data sources, such as TencentDB and CLS. This makes the most out of the strengths of each product through convenient data flows.


Service Benefits

  • Out-of-the-box: Unnecessary Ops tasks and costs are saved.
  • Metadata management: Multiple data sources are supported to unify metadata management and break through data silos.
  • Full coverage: Data Lake Compute comprehensively covers data analysis and application scenarios, specifically, data integration, synergy, scheduling, development, and governance.
Agile Setup of a Data Middleend

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.


Typical Use Cases

Cross-Business Federated Data Query

Enterprise departments and business lines often use different data architectures for their specific business systems. This means business data is dispersed in different storage systems, for example, transaction data in relational databases, active data in Redis, and historical records in object storage. With Data Lake Compute, you can align and analyze heterogeneous data from multiple sources to utilize your cross-business data more quickly.


Service Benefits

  • Out-of-the-box: There is no need to set up data transfer pipelines, so unnecessary Ops and costs are saved.
  • Secure and efficient: The permission management system is unified and refined to the column level, making queries super fast.
  • Easy-to-use: Cross-business analysis can be easily implemented without programming language adaptation.
Agile and Federated Data Lake Analysis

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.


Typical Use Cases

Business Growth Empowered by Data

Data Lake Compute offers native machine learning capabilities based on a sophisticated machine learning platform to provide a complete smart analysis solution. It helps solve your real-world business issues, such as smart recommendation and recall policies, and empower your business growth. Machine learning scenarios are often susceptible to problems like large data volumes, slow model training, and poor algorithm results. With this solution, you can enjoy out-of-the-box machine learning algorithm models to create data-driven models and predict business outcomes. You can also use its BI capabilities for efficient business analysis and improved operational efficiency.


Service Benefits

  • Ease of use: The service is seamlessly connected to Tencent Cloud's machine learning platform, giving you access to a wealth of models and APIs.
  • Data standardization: Unified data management and governance provide more standardized data for data operations.
Rich and Diversified Data Lake Portfolio
Pricing

Data Lake Compute can be billed by scanned data volume or usage in a pay-as-you-go manner. It can also be monthly subscribed. For more information, see Billing Overview.