Secure and Reliable
Integrates with Database Security Service (DBSS) to better protect user privacy and data security with network isolation and security group rule setting options. Adopts HA design and transparent data encryption to ensure high data and system reliability.
Easy to Use
A unified console helps you easily manage data warehouses and focus on data and service. DWS is compatible with Oracle, PostgreSQL, and Teradata so you have the freedom to choose. Simple-to-use database migration tool allows you to smoothly move heterogeneous databases over with complete confidence.
Supports real-time data import to databases, T+0 agile service analysis and decision-making, and correlation analysis on at-scale data within seconds. Provides enterprise-class capabilities such as OLAP analysis, statistics analysis, and self-service analysis.
Various Import Modes
Batch import of data from OBS and MRS adds speed and efficiency. Working with DIS, CS, and DLI, DWS helps you quickly and conveniently import streaming data. The service also uses third-party ETL and CDM for data migration and supports real-time data writing using Copy interfaces driven by JDBC.
Data Warehouse Migration
The data warehouse is an important data analysis system for enterprises. As the service volume grows, performance of self-built data warehouses cannot meet the actual service requirements due to their poor scalability and high costs. As an enterprise-class data warehouse on the cloud, DWS features high performance, low cost, and easy scalability, satisfying requirements in the big data era.
DWS provides various migration tools to ensure seamless migration of popular data analysis systems such as Teradata, Oracle, MySQL, SQL Server, PostgreSQL, Greenplum, and Impala.
DWS supports the SQL 2003 standard and stored procedures. It is compatible with some Oracle syntax and data structures, and can be seamlessly interconnected with common BI tools, smoothing service migration efforts.
DWS supports data encryption and interconnection with DBSS to ensure data security on the cloud, as well as automatic full and incremental backup of data to improve data reliability.
Enhanced ETL + Real-Time BI Analysis
The data warehouse is the pillar of the BI system for collecting, storing, and analyzing massive volumes of data. It powers business decision analysis for the IoT, finance, education, mobile Internet, and O2O industries.
Ability to import data in batches in real time from multiple data sources.
Cost-effective PB-level data storage and response to correlation analysis of trillions of data records within seconds.
Real-time consolidation of service data to produce actionable insights in operational decision-making.
Real-Time Data Analysis
In the mobile Internet and IoT domains, huge volumes of data must be processed and analyzed in real time to extract the full value from data. The quick data import and query capabilities of DWS accelerate data analysis capabilities to enable real-time ingestion, processing, and value generation.
Data from IoT and Internet applications can be written into DWS in real time after being processed by the stream computing and AI services.
Device monitoring, control, optimization, supply, self-diagnosis, and self-healing based on data analysis and prediction.
You can conduct correlation analysis on results of image and text data analysis (by AI services) and other service data on DWS.
May 15, 2017
Aug 22, 2017
MapReduce data loading
Aug 24, 2017
Nov 24, 2017
PG compatibility enhancement
Nov 26, 2017
Support for disk-intensive flavors
Mar 6, 2018
Automatic incremental snapshot
May 17, 2018
Adaptive resource management
Sept 30, 2018
Interconnection with DBSS
Oct 01, 2018
Support for PostGIS
Oct 03, 2018
Ability to use DWS Express to query data in data lakes (OBS)
Oct 20, 2018
Release of computing-intensive DC flavors (performance improved by several times)
Nov 13, 2018
Support for JAVA UDF
Nov 15, 2018
Intelligent resource management: memory adaptation & SQL self-tuning
Nov 17, 2018
Automatic collection of statistics and estimation of date type statistics
Jan 30, 2019
Transparent encryption and decryption
Feb 01, 2019
Cluster resource management with enterprise projects and fine-grained policies
Provides various functions to improve the reliability of data warehouse clusters.
Provides high-performance data warehouses dedicated for enterprises.
Built-in redundancy at the instance and data level avoids potential single points of failure (SPOFs), adding robustness to the service mix.
Provides multiple data replicas and supports manual data backup to OBS.
Automatically isolates faulty nodes, uses the replica to recover data, and supports node replacement.
Automatic incremental backup ensures data reliability at zero cost.
Uses a MPP-based computing framework, and supports hybrid row-column storage and vectorized executors, as well as SQL 03 analysis functions.
Adopts in-memory computing, MPP and SMP technologies, and LLVM, improving performance by 2-10 times.
Optimizes the communication between large-scale clusters based on telecommunication technologies, improving data transmission efficiency between compute nodes.
Cost-based optimizer generates an optimal execution plan based on cluster scale and data volume for supercharged efficiency.
Supports comprehensive SQL capabilities and smooth application migration.
Controls service usage and status.
Supports SQL 92 and SQL 2003 standards, complete transaction processing capabilities, and stored procedures.
One-click schema migration tool and SQL code conversion for heterogeneous databases like Oracle and MySQL.
Compatible with the PostgreSQL ecosystem and supports interconnection with mainstream database ETL and BI tools provided by third-party vendors.
Compatible with Oracle, PostgreSQL, and Teradata.
Integrates with CTS to allow you to audit all operations performed on the DWS management console and API calls.
Integrates with Cloud Eye to allow you to monitor compute nodes and databases in the cluster.
Records all SQL operations, involving connection attempts, queries, and database changes.