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Tencent Cloud DataBuddy

ドキュメントTencent Cloud DataBuddyData IntegrationList of Data SourcesData Source Overview

Data Source Overview

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最終更新日: 2026-10-09 16:09:17
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Overview

DataBuddy data ingestion continuously expands the supported data source types, covering five major categories: relational databases, big data storage, semi-structured data, NoSQL databases, and message queues. This document summarizes the currently supported data source types and the support status of each data source across different data ingestion paths, helping you quickly determine whether a target data source is available and choose an appropriate ingestion method.
Data sources are registered with DataBuddy as data source connections. For details, see Data Source Management. For specific connection configuration items of each data source, refer to the corresponding section in the data source list.
DataBuddy data sources provide four types of ingestion scenarios: offline synchronization, real-time synchronization, file upload, and direct analysis. Offline synchronization and real-time synchronization are distinguished by two directions: read (source-side ingestion) and write (destination-side writing). DataBuddy focuses primarily on read, with the destination fixed as the built-in DataBuddy TCLake.

Data Source Type Overview

The following table summarizes the ingestion capabilities of each data source by data source type. Offline integration and real-time integration are distinguished by two directions: read and write. Read indicates that the data source can be ingested as a source, and write indicates that it can be written to as a destination. DataBuddy focuses primarily on read, with the destination fixed as the built-in DataBuddy TCLake. Direct analysis indicates that the data source supports direct queries through Linked Catalog, which analyzes source data directly without landing it in the lake.
Data Source Type
Data Source
Offline Integration Read
Offline Integration Write
Real-Time Integration Read
Real-Time Integration Write
Direct Query Analysis
Relational databases
MySQL
✓
✓
✓
-
✓
Relational databases
Tencent Cloud MySQL
✓
-
✓
-
✓
Relational databases
TDSQL-C MySQL
✓
-
✓
-
✓
Relational databases
PostgreSQL
✓
-
✓
-
✓
Relational databases
Oracle
✓
-
✓
-
-
Relational databases
SQL Server
✓
-
✓
-
-
Relational databases
TDSQL MySQL
✓
-
-
-
✓
Relational databases
TDSQL PostgreSQL
✓
-
-
-
-
Relational databases
IBM DB2
✓
-
-
-
-
Relational databases
DM Database
✓
-
-
-
-
Relational databases
Greenplum
✓
-
-
-
-
Relational databases
GBase
✓
-
-
-
-
Relational databases
GaussDB
✓
-
-
-
✓
Relational databases
TiDB
✓
-
-
-
-
Relational databases
OceanBase
✓
-
-
-
-
Big data storage
HDFS
✓
-
-
-
-
Big data storage
HBase
✓
✓
-
-
-
Big data storage
Hive
✓
-
-
-
-
Big data storage
Kudu
✓
-
-
-
-
Big data storage
ClickHouse
✓
✓
-
-
-
Big data storage
TCHouse-C
✓
-
-
-
-
Big data storage
TCHouse-D
✓
-
-
-
✓
Big data storage
TCHouse-X
✓
-
-
-
-
Big data storage
TCHouse-P
✓
-
-
-
-
Big data storage
Doris
✓
-
-
-
✓
Big data storage
StarRocks
✓
-
-
-
✓
Big data storage
Iceberg
✓
-
-
-
-
Big data storage
Hudi
✓
-
-
-
-
Big data storage
TDengine
✓
-
-
-
-
Big data storage
BigQuery (Overseas)
✓
-
-
-
-
Semi-structured data
FTP
✓
-
-
-
-
Semi-structured data
SFTP
✓
-
-
-
-
Semi-structured data
COS
✓
✓
-
-
-
Semi-structured data
REST API
✓
-
-
-
-
Semi-structured data
File System
✓
-
-
-
-
Semi-structured data
Amazon S3
✓
-
-
-
-
NoSQL databases
MongoDB
✓
-
✓
-
-
NoSQL databases
TencentDB for MongoDB
✓
-
✓
-
-
NoSQL databases
Elasticsearch
✓
-
-
-
-
NoSQL databases
Tencent Cloud Elasticsearch
✓
-
-
-
-
NoSQL databases
CTSDB / InfluxDB
✓
-
-
-
-
Message queue
Kafka
✓
-
✓
-
-
Message queue
CKafka
✓
-
✓
-
-

References

Supported Access Solutions
Supported Data Sources and Read Capabilities
Data Source Management
Real-Time Whole-Database Multi-Table Task Configuration
Real-Time Database/Table Sharding Task Configuration
前の記事へ: Data Source Management次の記事へ: Kafka Data Sources

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