GaussDB(DWS) uses the GaussDB database kernel and is compatible with PostgreSQL 9.2.4. It transforms from a single OLTP database to an enterprise-level distributed OLAP database oriented to massive data analysis based on the massively parallel processing (MPP) architecture.
Unlike conventional data warehouses, GaussDB(DWS) excels in massive data processing and general platform management with the following benefits:
Ease of use
Visualized one-stop management
GaussDB(DWS) allows you to easily complete the entire process from project concept to production deployment. With the GaussDB(DWS) management console, you can obtain a high-performance and highly available enterprise-level data warehouse cluster within several minutes. Data warehouse software or data warehouse servers are not required.
With just a few clicks, you can easily connect applications to the data warehouse, back up data, restore data, and monitor data warehouse resources and performance.
Seamless integration with big data
Without the need to migrate data, you can use standard SQL statements to directly query data on HDFS and OBS.
Heterogeneous database migration tools
GaussDB(DWS) provides various migration tools to migrate SQL scripts of Oracle and Teradata to GaussDB(DWS).
Cloud-based distributed architecture
GaussDB(DWS) adopts the MPP-based database so that service data is separately stored on numerous nodes. Data analysis tasks are executed in parallel on the nodes where data is stored. The massively parallel data processing significantly improves response speed.
Query response to trillions of data records within seconds
GaussDB(DWS) improves data query performance by executing multi-thread operators in parallel, running commands in registers in parallel with the vectorized computing engine, and reducing redundant judgment conditions using LLVM.
GaussDB(DWS) provides you with a better data compression ratio (column-store), better indexing (column-store), and higher point update and query (row-store) performance.
Fast data loading
GDS is a tool that helps you with high-speed massively parallel data loading.
On-demand scale-out: With the shared-nothing open architecture, nodes can be added at any time to enhance the data storage, query, and analysis capabilities of the system.
Enhanced linear performance after scale-out: The capacity and performance increase linearly with the cluster scale. The linear rate is 0.8.
Service continuity: During scale-out, data can be added, deleted, modified, and queried, and DDL operations (DROP/TRUNCATE/ALTER TABLE) can be performed. Online table-level scale-out ensures service continuity.
Support for the atomicity, consistency, isolation, and durability (ACID) feature, which ensures strong data consistency for distributed transactions.
Comprehensive HA design
All software processes of GaussDB(DWS) are in active/standby mode. Logical components such as the CNs and DNs of each cluster also work in active/standby mode. This ensures data reliability and consistency when any single point of failure (SPOF) occurs.
GaussDB(DWS) supports transparent data encryption and can interconnect with the Database Security Service (DBSS) to better protect user privacy and data security with network isolation and security group rule setting options. In addition, GaussDB(DWS) supports automatic full and incremental backup of data, improving data reliability.