Tablestore Node.js SDK supports operations in the Wide Column model.
Feature list
Before you use the SDK features, you need to initialize a client. The following table describes the features supported by the Node.js SDK.
Feature type | Operation | Description |
You can create a data table to store data. You can configure auto-increment primary key columns when you create a data table. | ||
Updates the configurations of a data table. | ||
View the names of all data tables in an instance. | ||
Queries the configurations of a data table. | ||
You can delete a data table. | ||
Write data to the data table. | ||
Read data from the data table. | ||
Delete data from the data table. | ||
Filter the read results on the server side based on the conditions in the filter. | ||
Update data in a table only when the specified conditions are met. Otherwise, the update fails and an error is returned. | ||
The atomic counter feature allows you to specify a column as an atomic counter and perform atomic counter operations on the column. | ||
After you enable local transaction for a data table, you can create a local transaction based on a partition key value. | ||
You can create a search index for a data table. | ||
Query search indexes that are created for a table. | ||
Update the time to live (TTL) of a search index. | ||
Query the description of a search index, including the information about the fields in the search index and configurations of the search index. | ||
Delete a specified search index. | ||
Basic query types include match all query, term query, terms query, prefix query, range query, wildcard query, exists query, collapse (deduplicate), geo query, and nested query. | ||
Query conditions can contain one or more subconditions. Data is determined to meet the query conditions based on the subconditions. | ||
When you query data by using search indexes, you can specify a sorting method to sort the returned data. When many rows are returned, you can use offset-based pagination or token-based pagination to quickly locate the data you want. | ||
You can perform operations such as finding the minimum value, finding the maximum value, calculating the sum, calculating the average, counting rows, counting distinct values, grouping by field values, grouping by range, grouping by geographical location, and grouping by filter conditions. Multiple aggregation features can be combined to meet complex query requirements. | ||
Tablestore provides match query and phrase query to implement full-text index features. Queries match data based on tokenization and support summary and highlighting features to highlight query terms. | ||
You can use the k-nearest neighbor (KNN) vector query feature to perform an approximate nearest neighbor search based on vectors. This way, you can find data items that have the highest similarity to the vector that you want to query in a large-scale dataset. | ||
When you do not need to maintain the order of the entire result set, you can use the parallel export feature to return all matched data at a faster speed. | ||
Create a secondary index for a data table. | ||
You can query data in a secondary index by reading a single row of data or reading data whose primary key values are within a specific range. If the required attribute columns are included in the secondary index, data can be directly read from the secondary index. Otherwise, data must be read from the data table. | ||
Delete a specified secondary index from a data table. | ||
Create a mapping relationship for an existing table or index. | ||
Add or remove attribute columns in an existing mapping table. | ||
Delete one or more mapping tables | ||
List the mapping tables in the current database. | ||
Query the description of a table, such as field names and field types. | ||
Query the index description of a table. | ||
You can use the SELECT syntax to query data in a table. |
References
For more information about how to handle Tablestore errors, see Error handling.