What is Tablestore?

Term

Description

Region

A region is a physical data center. Tablestore is deployed in multiple Alibaba Cloud regions. You can select a region to use the Tablestore service as needed. For more information, see Regions and zones.

Read/write throughput

Read throughput and write throughput are measured in read capacity units and write capacity units. A capacity unit (CU) is the smallest billing unit for read and write operations. For more information, see Read/write throughput.

Instance

An instance is an entity used to manage and use the Tablestore service. Each instance is equivalent to a database. Tablestore performs access control and resource metering for applications at the instance level. For more information, see Instances.

Endpoint

Each instance has an endpoint. An application must specify the endpoint when it performs operations on tables and data. For more information, see Endpoints.

Data lifecycle

Time to live (TTL) is a property of a data table. It specifies the retention period of data in seconds. Tablestore runs in the background to clear expired data. This reduces your data storage space and storage costs. For more information, see Data versions and time to live (TTL).

Model

Description

Wide table model

This model is similar to the Bigtable and HBase models. It can be used in various scenarios, such as metadata and big data. It supports features such as data versions, TTL, auto-increment primary key columns, conditional updates, local transactions, atomic counters, and filters. For more information, see Wide Column model.

TimeSeries model

This model is designed based on the characteristics of time series data. It can be used in scenarios such as IoT device monitoring, device data collection, and machine monitoring data. It supports features such as automatic creation of time series metadata indexes and a wide range of time series query capabilities. For more information, see TimeSeries model.

Message model

This model is designed for message data scenarios. It can be used in message scenarios such as instant messaging (IM) and feed streams. It meets the requirements of message scenarios for message ordering, massive message storage, and real-time synchronization. It also supports full-text search and multi-dimensional composite queries. For more information, see Timeline model.

Billing mode

Description

VCU mode (formerly reserved mode)

You can purchase reserved VCUs in advance based on resource evaluation results, or enable elastic capacity and pay for consumed computing performance on a pay-as-you-go basis. You can use reserved VCUs and elastic capacity together to save costs.

• When you purchase reserved VCUs, you must pay for compute resources in advance. Tablestore provides fixed computing power based on the purchased reserved VCUs. The unit is VCU.

• After you enable elastic capacity for an instance, the instance enters Serverless mode. You can pay for consumed computing performance based on actual usage without purchasing compute resources in advance.

This mode helps you save on compute resource costs. This mode also lets you control overall resource usage by configuring an upper limit for elastic capacity or disabling elastic capacity. This prevents extra fees caused by unusual traffic. This makes it a better choice for scenarios that require cost control.

Billable items include computing power, data storage, cross-region replication traffic, and outbound public traffic, where data storage includes high-performance storage, Capacity storage, and search index storage. For more information, see VCU mode (formerly Reserved mode).

CU mode (formerly pay-as-you-go mode)

You are charged for resources such as real-time read/write throughput and storage space. You do not need to plan hardware resource consumption in advance.

This mode is suitable for scenarios where workloads fluctuate significantly and unpredictably. The elastic capacity provided by CU mode (formerly pay-as-you-go mode) ensures that your application can handle traffic bursts. This makes it a better choice for scenarios that require high service stability.

Billable items include read throughput, write throughput, data storage, cross-region replication traffic, and outbound public network traffic. For more information, see CU mode (formerly Pay-As-You-Go mode).

Method

Description

Console

Alibaba Cloud provides a web service page that lets you easily operate Tablestore. For more information, see the Tablestore console.

SDK

Supports mainstream development languages such as Java, Go, Python, Node.js, .Net, and PHP. For more information, see SDK Reference.

Command line interface

Lets you operate Tablestore using simple commands. For more information, see Command line interface.

Analytical tool

Applicable model

Operation

Description

MaxCompute

Wide table model

Use MaxCompute

You can create a foreign table for a data table in Tablestore using the MaxCompute client, which lets you access the data in Tablestore.

Spark

Wide table model

Use the Spark compute engine

When you use the Spark compute engine, you can access Tablestore through E-MapReduce SQL or DataFrame programming.

Hive or HadoopMR

Wide table model

Use Hive or HadoopMR

Use Hive or Hadoop MapReduce to access data in Tablestore.

Function Compute

Wide table model

Use Function Compute

Use Function Compute to access Tablestore and perform real-time computing on Tablestore incremental data.

Flink

• Wide table model

• Time series model

Use Flink

You can use Real-time Compute Flink to access source tables, dimension tables, or sink tables in Tablestore to perform real-time computing and analysis on big data.

PrestoDB

Wide table model

Use Tablestore with PrestoDB

After connecting PrestoDB to Tablestore, use SQL to query and analyze data in Tablestore, write data to Tablestore, and import data into Tablestore through PrestoDB on Tablestore.

Tablestore search index

Wide table model

Search index

Search index uses inverted indexes and columnar storage to address complex multidimensional queries and statistical analysis for big data. When your business requires queries on non-primary key columns, multi-column combined queries, fuzzy queries, or analytics such as finding maximum/minimum values, counting rows, or grouping data, define these attributes as fields in a search index and use it to query and analyze your data.

Tablestore SQL query

• Wide table model

• Time series model

Use SQL query

SQL query provides a unified access interface for multiple data engines. With the SQL query feature, you can access Tablestore data to run complex queries and perform efficient analysis.

Category

Data synchronization

Description

Data import

Synchronize MySQL data

Use DataX, DTS, Canal, or Tapdata Cloud to synchronize data from a MySQL database to Tablestore.

Sync Kafka data

Use the Tablestore Sink Connector to batch import data from Apache Kafka into data tables or time series tables in Tablestore.

Sync Oracle data

Using the Tapdata Cloud visualization interface, sync Oracle data to Tablestore in real time.

Sync HBase data

Synchronize full data from an HBase database toTablestore using DataX.

Sync MaxCompute data

Use DataWorks to sync full data from MaxCompute to Tablestore.

Sync data in Tablestore data tables

Use Tunnel Service, DataWorks, or DataX to synchronize data from a Tablestore data table to another data table.

Sync data in a Tablestore time series table

Use the DataWorks tool to synchronize full data or incremental data from a Tablestore time series table to another time series table.

Data exporting

Sync to MaxCompute

Use DataWorks to export full data or incremental data from Tablestore to MaxCompute.

Sync to OSS

Use DataWorks to export full or incremental data from Tablestore to OSS.

Sync to a local file

Use the command line interface or DataX to download data directly to a local file. You can also use DataWorks to sync data to OSS, then download the data from OSS to a local file.