HybridDB for MySQL

HybridDB for MySQL is a Hybrid Transaction/Analytical Processing (HTAP) relational database service that supports online transaction processing (OLTP) and online analytical processing (OLAP) of large amounts of data.

HybridDB for MySQL is a Hybrid Transaction/Analytical Processing (HTAP) relational database service that supports online transaction processing (OLTP) and online analytical processing (OLAP) of large amounts of data. Initially known as PetaData, this service uses only one dataset for both OLTP and OLAP, without the need to provide multiple replicas for transaction and data analysis which significantly reduces data storage costs.

Benefits

OLTP
The high throughput of HybridDB for MySQL enables you to manage highly concurrent OLTP workloads.
OLAP
Only one set of data is required for both transaction processing and analysis.
High Compatibility with SQL
HybridDB for MySQL is compatible with MySQL syntax and Oracle analytic functions. It fully supports TPC-H and TPC-DS.
High Storage Capacity
HybridDB for MySQL provides data storage and compression services for terabytes or petabytes of data.

Features

  • HTAP

    OLTP

    The high throughput of HybridDB for MySQL enables you to manage highly concurrent OLTP workloads.

    OLAP

    Extracting, transforming, and loading data from online databases to data warehouses is no longer required. This significantly reduces the latency of data analysis.

  • Compatibility with SQL

    Compatibility with MySQL

    HybridDB for MySQL is compatible with the API of MySQL, the world's most popular open-source relational database.

    Support for Oracle

    HybridDB for MySQL supports common Oracle analytic functions. With these functions, this service is able to support a myriad of analytic applications.

  • Distributed Architecture

    Large Capacity

    HybridDB for MySQL provides data storage and compression services for terabytes or petabytes of data. It uses data blocks to compress and store data in order to reduce the costs.

    High Performance

    The capacity of processing distributed tasks increases linearly when the number of distributed nodes increases.

Scenarios

  • Data Analysis
  • High Capacity for Archiving Historical Data
IoT

IoT

Highly-concurrent and High-performance Data

HybridDB for MySQL supports highly-concurrent data writing, provides large storage space for sample data. It also supports SQL relational queries. HybridDB for MySQL is the best database service for IoT industries such as intelligent transportation systems, smart home systems, and industrial control systems.

Benefits

  • High Performance

    You can scale out the number of nodes to improve linearly the performance of handling tasks.

  • Large Capacity

    HybridDB for MySQL applies the distributed multi-node architecture and provides large storage space for terabytes or petabytes of data.

Data Analysis

Data Analysis

HTAP Relational Database

Only one set of data is required for both OLTP and OLAP. Without data ETL for traditional data warehouses, the storage costs and analysis latency are greatly reduced. By using HybridDB for MySQL, you are able to build a real-time analysis and decision support system.

Benefits

  • OLTP

    HybridDB for MySQL supports highly-concurrent real-time data writing and provides large storage space.

  • OLAP

    HybridDB for MySQL supports big data analysis.

High Capacity for Archiving Historical Data

High Capacity for Archiving Historical Data

Provides cost-effective databases with high storage capacity.

HybridDB for MySQL provides large storage space with low costs and supports data compression. It also supports SQL relational queries. HybridDB for MySQL is the relational database system with the most cost-effective storage for government, finance, industry, and scientific research.

Benefits

  • Large Capacity

    HybridDB for MySQL applies the distributed multi-node architecture and provides large storage space for terabytes or petabytes of data.

  • Cost-effectiveness

    HybridDB for MySQL supports data compression to greatly reduce storage costs.