Product Overview

Advantages Cloud Database Self-built Database
Price

No software/hardware investment required, multiple selections (high I/O edition and large-capacity edition) are available, and fees are charged on demand.

The cost of a single storage server is high (if master/slave mode is required, two devices need to be purchased to implement resource redundancy). Recruitment of professional DBA engineers is required.

Service availability

Up to 99.95% service availability; compliant with high industry standards. A professional team provides 24x7 service, 1-on-1 guidance, and QQ remote assistance.

Faults need to be rectified by users, and users need to build the master/slave mode and RAID.

Data reliability

Up to 99.9996% data reliability. It boasts a perfect automatic data backup mechanism with complete restoration (real-time hot backup, restoration of data at any time point within 5 days).

Users need to safeguard data reliability, which relies on hardware fault occurrence rates and technician database management skills.

Monitoring

It integrates about twenty professional database monitoring technologies and gives failure alerts, putting you at ease.

Users need to develop a database monitoring system and Ops personnel may have to troubleshoot failures during overtime.

Ops

Users do not need to worry about installation, deployment, version update, and troubleshooting for MongoDB; these are all taken care of by the cloud database Ops team.

Election behavior inside a cluster, troubleshooting, and data migration are completely transparent to users.

Users are responsible for installing the database and deploying the multi-mode replica set.

Users need to manually back up data and perform data restoration.

 

Function Description

Function Description
  • Powerful hardware provides performance guarantee.

    The physical model using the ultra-large memory and high-performance SSD to supports mass access.
    The instances of the high IO edition support a maximum access count of 30000 QPS.
High Availability
  • Real-time hot backup

    Two- or multiple-cluster hot backup; auto disaster recovery; auto active/standby switching and fault migration
    Preferentially reads data from the master database, just as with the local MongoDB, ensuring high concurrent reading capabilities
  • Auto disaster recovery

    Auto detects and migrates faults in case of breakdown. Active/standby switching and failovers are all handled automatically.
High Reliability
  • Data guarantee

    Up to 99.996% data reliability. At least two backup copies are provided to guarantee that your data is secure.
  • Data restoration

    With the help of cold backup and oplog, it is capable of restoring data to at any point in time within 3 days and dump cold backup data within 5 days.
 

Price

Type Specifications (1 Primary, 1 Secondary, and 1 Arbiter) Monthly Package (CNY) Specifications (1 Primary, 2 Secondary) Monthly Package (CNY)
High IO 1-core 2G 225 1-core 2G 325
High IO 2-core 4G 450 2-core 4G 650
High IO 2-core 6G 675 2-core 6G 975
High IO 4-core 8G 900 4-core 8G 1300
High IO 4-core 12G 1350 4-core 12G 1950
High IO 6-core 16G 1800 6-core 16G 2600
High IO 10-core 24G 2700 10-core 24G 3900
High IO 12-core 32G 3600 12-core 32G 5200
High IO 18-core 48G 5400 18-core 48G 7800
High IO 24-core 64G 7200 24-core 64G 10400
Master/Slave/Arbiter: 1.6 CNY/GB/month; 1 Primary/2 Secondary: 2.4 CNY/GB/month.
 

Application Scenarios

Common scenarios

Non-relational data structure also meets the requirements of various development scenarios and performance is no different from or even superior to the relational database.

Quick changing businesses

Business of start-up companies changes rapidly. Cloud MongoDB can cope with such changes incredibly well, with its elastic and flexible data modes.

High concurrent read/write operations

Cloud MongoDB excels in highly concurrent read/write performance; and is suitable for scenarios where high read/write concurrency is necessary.

Data analysis

Cloud Mongo internally supports map-reduction framework and can aggregate and analyze large amounts of data.