Tablestore:Features

Feature

Description

References

Operations on tables

You can list all data tables in an instance, create a data table, query and update the configurations of a data table, and delete a data table.

Operations on a data table

Basic data operations

You can call the PutRow, GetRow, UpdateRow, and DeleteRow operations to perform operations on a single row or call the BatchWriteRow, BatchGetRow, and GetRange operations to perform operations on multiple rows. You can read and write data in a table by calling an operation to perform operations on a single row or multiple rows in the table.

• Write data

• Read data

• Delete data

Max versions and TTL

You can use the max versions and TTL features to manage the lifecycle of your data to optimize storage efficiency and reduce costs.

Data versions and TTL

Auto-increment primary key column

You can specify a primary key column that is not the partition key as the auto-increment primary key column. If you write data to a table that contains an auto-increment primary key column, you do not need to specify values for the auto-increment primary key column. Tablestore automatically generates values for the auto-increment primary key column. The values generated for the auto-increment primary key column are unique and increase monotonically within a partition.

Configure an auto-increment primary key column

Conditional update

If you use conditional update, data in the table can be updated only when the conditions are met. If the conditions are not met, the update fails.

Conditional updates

Local transaction

You can create a local transaction for data that shares the same partition key value. After you read or write data within a local transaction, you can commit or abort the local transaction.

Local transactions

Atomic counter

This feature allows you to implement an atomic counter on a column, and provides real-time statistic data for online applications such as the number of page views (PVs) on various topics.

Use the atomic counter feature

Filter

Filters sort results on the server side. Only results that meet the filter conditions are returned. This feature effectively reduces the volume of transferred data and shortens the response time.

Configure a filter

Secondary index

You can create one or more index tables for a data table and perform queries by using the primary key columns of the index tables. Secondary indexes are classified into global secondary indexes and local secondary indexes.

• When you use a global secondary index, Tablestore automatically synchronizes data from the indexed columns and primary key columns of a data table to the columns of an index table in asynchronous mode. The synchronization latency can be measured in milliseconds.

• When you use a local secondary index, Tablestore automatically synchronizes data from the indexed columns and primary key columns of a data table to the columns of an index table in synchronous mode. You can immediately query the data from the index table after the data is written to the data table.

• Overview

• Methods:

  • Use secondary indexes in the Tablestore console

  • Get started with secondary indexes by using Tablestore SDKs

  • Use secondary indexes in the Tablestore CLI

Search index

Search indexes are used for multi-dimensional data queries and statistical analysis in big data scenarios based on inverted indexes and column stores. Search indexes support various query methods, including query based on non-primary key columns, full-text search, prefix query, fuzzy query, Boolean query, nested query, and geo query. Search indexes also support parallel scan and multiple aggregation operations. You can perform aggregation operations to obtain the maximum and minimum values, count and distinct count of rows, sums, and averages, and group results by specific conditions.

• Overview

• Features

• Get started with search indexes

• Manage indexes

• Query methods: Basic query, Query based on multiple conditions, Full-text search, and KNN vector query

• Aggregation

• Export data

SQL query

The SQL query feature provides a unified access interface for multiple data engines. You can use the SQL query feature to perform complex queries and analytics on data in Tablestore in an efficient manner. You can also use indexes in combination with the SQL query feature to optimize queries.

• Overview

• Use the SQL query feature in the Tablestore console

• Use Tablestore SDKs to use the SQL query feature

• Use Java Database Connectivity (JDBC)

  • Use JDBC to access Tablestore

  • Use Hibernate to query data by executing SQL statements

  • Use MyBatis to query data by executing SQL statements

• Use the Tablestore driver for Go to query data by executing SQL statements

Tunnel Service

Tunnel Service provides tunnels that are used to export and consume data in full, incremental, and differential modes. After you create a tunnel, you can use it to consume historical and incremental data of a table.

• Overview

• Quick start

• Use Tunnel Service by using Tablestore SDKs

Data security

By default, you can access Tablestore by using the Tablestore console or over the classic network or VPC endpoint. You can bind a VPC to a Tablestore instance and change the network types of the instance to allow access to the instance only over the VPC. This enhances access security.

Tablestore provides the data encryption feature to encrypt data when the data is written to a data table. This ensures the security of table data. When you create a data table, you can configure table encryption.

• Network security management

• Data encryption

Data delivery

Tablestore uses data delivery to deliver full or incremental data to Object Storage Service (OSS) in real time. This feature is ideal for building data lakes as it enables Tablestore to store historical data in OSS at lower costs while Tablestore implements offline or quasi-real-time analysis of larger amounts of data.

• Overview

• Use the Tablestore console to deliver data to OSS

• Use Tablestore SDKs

Data visualization

Tablestore supports two data visualization tools: DataV and Grafana. These tools can be used to visualize data in Tablestore.

• Connect Tablestore to Grafana

• Connect Tablestore to DataV-Board 6.0

Monitoring and alerting

You can view monitoring information about Tablestore resources to monitor resource usage. You can also configure alert rules for important metrics of the resources. This way, you can receive notifications of metric anomalies and troubleshoot the errors at the earliest opportunity.

• View monitoring data in the Tablestore console

• Configure alert rules for monitoring metrics

Backup and restoration

You can use Cloud Backup to back up data in Tablestore instances on a regular basis and restore the lost or damaged data at the earliest opportunity. You can use Cloud Backup to back up full and incremental data. Cloud Backup supports the data redundancy mechanism to increase the data reliability of storage vaults.

• Back up data in Tablestore

• Restore data to Tablestore

HBase support

Tablestore HBase Client can be used to access Tablestore by using Java applications built on open source HBase APIs.

• Tablestore HBase Client

• Getting started

Audit log

You can use the audit log feature to query and analyze the logs of operations performed on tables and indexes in a Tablestore instance.

• Overview

• Enable the audit log feature

• Query and analyze audit logs

Feature

Description

References

Operations on tables

You can list all time series tables in an instance, create a time series table, query and update the configurations of a time series table, and delete a time series table.

• Use the TimeSeries model in the Tablestore console

• Use the Tablestore CLI

• Use the TimeSeries model by using Tablestore SDKs

Read and write time series data

You can write time series data into a time series table in batches. After data is written to the time series table, you can specify time series identifiers to query the data in the time series within the specified time range.

Time series retrieval

You can retrieve a time series in a time series table by using composite conditions. After the time series is retrieved, you can call Tablestore API operations to further query data in the time series.

SQL query and analysis

You can use SQL statements to query time series data. In an SQL statement, you can filter time series by specifying metadata conditions and aggregate data based on different dimensions.

In addition, you can query only the metadata of time series in SQL. This way, you can manage the metadata of time series by using SQL.

Use SQL to query time series data

Connection with Grafana

After you add a Tablestore data source to Grafana, Grafana displays real-time data on a dashboard.

Connect Tablestore to Grafana

Feature

Description

References

Operations on tables

• You can create or delete a Meta table and its indexes.

• You can create or delete a Timeline table and its indexes.

Table operations

Meta management

You can call operations such as Insert, Delete, Update, Read, and Search to manage Meta data.

Meta management

Timeline management

You can call the operations for fuzzy query and Boolean query to manage Timeline data.

Timeline management

Queue management

The Queue instance manages a message queue that corresponds to an identifier of a TimelineStore. This instance provides operations such as Store, StoreAsync, BatchStore, Delete, Update, UpdateAsync, Get, and Scan.

Manage queues