Tablestore is a distributed NoSQL data storage service built on Alibaba Cloud's Apsara distributed computing system, which comes with 99.99% high availability and 99.999999999% data reliability. Tablestore enables seamless expansion of data size and access concurrency through data sharding and server load balancer technologies, providing storage of and real-time access to massive structured data.
Benefits
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High Reliability
Three copies of data with high consistency, full host, service high availability and data high reliability.
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Low-cost
Elastic resources, Pay-As-You-Go billing, and O&M with no additional costs.
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Highly Elastic
Distributed architecture, single table auto scaling, support of 10-PB-level data and 10-million-level access concurrency.
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Easy to Analyze
Provides full/incremental data tunnels, seamlessly interconnecting with various products for big data analysis and real-time stream computing.
Features
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Powerful and flexible security
Multi-dimensional and multi-level security protection and resource access management to ensure data security
Provides table-level and API-level authentication and authorization mechanisms, supports STS temporary authorization, custom permission authentication, and primary/sub accounts
Flexible authentication and authorization mechanisms
Multi-network support
Supports Internet, ECS Intranet, and VPC private network accessing, and provides network resource access management
Resource isolation
There is a system to separate access to resources by user level.
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Convenient and flexible use
Provides standard RESTful APIs and multilingual SDKs and supports multi-version data and TTL features
Flexible access
Provides standard RESTful APIs, a wide range of SDKs and client tools
Flexible use
With a sparse table structure, the number and types of columns in each row can be different from each other and attribute columns do not need to be pre-defined
Data management
Supports TTL management and multi-version management
Convenient use
The product console provides instance/table-level monitoring data access (QPS, latency, and number of requests)
HBase support
The official Tablestore HBase Client supports HBase services
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Distributed architecture and big data models
Utilizing a distributed architecture, automated server load balancer and hot-spot migration mechanisms, Tablestore provides unlimited data storage and access concurrency
Large scale
10-PB-level data volume for a single table, trillion records and a capacity of 10-million-level TPS
O&M free
Automated server load balancer and hot-spot migration, without the need for manual intervention
Effective storage engine
High-throughput write capacity and stable and predictable read/write performances based on shared storage
High security
Three copies of data ensure high consistency, which is designed based on a standard of 99.999999999% data reliability
High availability
A shared storage architecture ensures fast detection and fast recovery of single point of failure, which is designed based on a standard with 99.99% availability
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Complete big data computing system
Supporting various big data computing platforms and real-time stream computing and provides powerful data analysis capacity
Combination of storage and computing
Implement a data loop of online storage, offline computing and real-time analytics
Big data ecosystem
Supports MaxCompute direct read/write and access from various open-source components such as EMR Hadoop, Spark, Hive, and Flink
Real-time computing
Supports Alibaba Cloud StreamCompute and Function Compute, which perform real-time computing for Tablestore incremental data
Data tunnel
Supports Alibaba Cloud Data Integration and full/incremental data tunnels
Multi-industry solutions
Solutions for social IM, gaming, finance, IoT and logistics
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Advanced functions simplify the application architecture
Provides various features such as PK auto-incrementing column and streaming read
PK auto-incrementing column
Solves problems with high concurrency in social IM and feed streams
Effective streaming read interface
Handles high concurrent reading and storage of massive data, and supports real-time computing of incremental data
Common Scenarios
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Data Storage & Analysis
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Social Feed Stream
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Finance
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IoV Data Storage
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IoT Time Series Data
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E-commerce
Massive Data Storage & Analysis
A loop of storage and processing of massive data and online services
Tablestore provides low-cost, low-latency, and high-concurrency storage and online access of massive data, as well as incremental and full data tunnels, with support for SQL direct read and write on MaxCompute and other big data analysis platforms. Effective incremental streaming read interface allows easy real-time stream computing of data.
Advantages
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Large-scale
10-PB-level data volume for a single table, trillion records and a capacity of 10-million-level TPS
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Computing Integration
Supporting various big data computing platforms, stream computing and real-time computing services
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Low-cost
High-availability massive message storage and multi-terminal message synchronizationElastic Pay-As-You-Go resources provide instances with two specifications, high performance and high capacity, meeting the needs of different services
Social Feed Stream
Storage of massive messages with high availability, high concurrency and stable latency
Tablestore can be used to store IM messages and social feed stream information such as comments, follow-up posts and likes. The elastic resources stored in Tablestore are billed under the Pay-As-You-Go model and at a relatively low cost Tablestore can meet the needs of applications that feature significant traffic fluctuations and high concurrency while requiring low latency.
Advantages
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Simplifying High Concurrency Architecture
A single table containing trillion records easily stores full history transaction recordsBuilt-in PK auto-incrementing column simplifies external system dependencies
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Stable Performance
A design standard with 99.999999999% data reliability and three copies of the data ensures data securityThe average read/write performance for high performance instance is less than 10 ms/instance, which is not affected by data size
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Massive Message Storage
High-availability massive message storage, and multi-terminal message synchronization
Products
Financial Transactions and Risk Control
Storage and real-time query of massive transaction records and user models
The low latency, high concurrency, elastic resources and Pay-As-You-Go billing method of this service enables your risk control system to always operate in optimal conditions, allowing you to strictly control transaction risks. Meanwhile, the flexible data structure allows your business model to rapidly evolve to meet market demands.
Advantages
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Scalability
A single table containing trillion records easily stores full history transaction records
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Reliability
A design standard with 99.999999999% data reliability, and three copies of data ensure the data security
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Flexible Usage
Schemafree model and attribute column fields (which are added as needed) for rapid service development
Products
IoV Data Storage
Massive, efficient and flexible IoV data storage
A single table can store petabytes of data without distributing data in separate databases and tables, which simplifies the service logic. The schema-free data model enables easy access to the monitoring data of different vehicle-mounted devices. Tablestore can be seamlessly integrated with multiple big data analysis platforms and real-time computing services for fast real-time online query and service report analysis.
Advantages
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Data Scale
A single table can store tens of petabytes of data without distributing data in separate databases and tables, which simplifies the service logic
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Stable Performance
The query performance of vehicle conditions and tracks is stable and predictable
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Flexible Use
The schema-free data model enables easy access to the monitoring data of different vehicle-mounted devices
Products
IoT Time Series Data
Massive data storage and effective query and Analysis
With a single table capable of storing petabytes of data and processing thousands of queries per second (QPS), Tablestore makes it easy to store the time series data of IoT devices and monitoring systems. The big data analysis SQL direct read function and the efficient incremental streaming read interface provide an easy way for offline data analysis and real-time stream computing.
Advantages
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Data Scale
A single table can store tens of petabytes of data, meeting the needs of data write and storage of ultra large-scale IoT devices and monitoring systems
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Data Analysis
Through interconnecting with multiple offline, stream data analysis platforms, a piece of data can satisfy analysis and computing scenarios for different services
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Low-cost
Pay-As-You-Go, low cost, and support for TTL management
Products
E-commerce Orders and Ad Recommendations
Database for massive transaction orders and user recommendations
Using Tablestore for a large number of historical transaction orders makes it possible for you to deal with high data volume and access performance with ease. Combined with MaxCompute, Tablestore enables precision marketing, elastic resource storage, and Pay-As-You-Go billing, so that you can easily cope with peak hours when all your users are online.
Advantages
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Flexible Resources
Auto scaling of data size and access concurrency meets the needs of access during peaks and valleys
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Computing Integration
Supports various big data analysis platforms for direct user analytics
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Fast Query
Fast query of massive transaction orders
Products
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