TDCH TeraData

TDCH, short for Teradata Connector for Hadoop, is a product developed by Teradata Corporation to facilitate data integration and data transfer between Teradata data warehouses and Hadoop ecosystems. It allows organizations to leverage the power of both Teradata and Hadoop for big data analytics and processing. Here are some key points about TDCH:

1. Purpose: TDCH enables seamless data movement between Teradata and Hadoop. It allows users to extract data from Teradata, load it into Hadoop HDFS, and vice versa, making it easier to perform big data analytics on Teradata data within the Hadoop ecosystem.

2. Hadoop Ecosystem Support: TDCH is compatible with various components of the Hadoop ecosystem, including Hadoop MapReduce, Apache Hive, Apache Pig, and Apache Spark. It provides connectors and utilities for different Hadoop technologies.

3. Data Loading and Unloading: TDCH supports data loading (extracting data from Teradata and loading it into Hadoop) and data unloading (extracting data from Hadoop and loading it into Teradata). This bidirectional data transfer is crucial for integrating data from multiple sources.

4. Parallel Processing: TDCH is designed for high-performance data transfer and integration. It leverages parallel processing capabilities to efficiently move data between Teradata and Hadoop, reducing transfer times.

5. Data Format Support: TDCH supports various data formats, including Avro, Parquet, SequenceFile, and delimited text files. Users can specify the format for data extraction and loading based on their requirements.

6. Security: TDCH includes security features to protect data during the transfer process. It supports encryption and authentication mechanisms to ensure data security and compliance with security policies.

7. Teradata SQL Support: Users can leverage Teradata SQL for defining the data extraction and loading operations, making it easier for Teradata users to work with TDCH.

8. Data Transformation: TDCH allows users to perform data transformations during the transfer process. This is particularly useful for data cleansing, formatting, and structuring data to meet specific requirements.

9. Batch and Real-Time Integration: TDCH supports batch data integration as well as real-time integration for organizations that require near-real-time access to their data.

10. Hadoop Distribution Compatibility: TDCH is typically compatible with popular Hadoop distributions such as Apache Hadoop, Cloudera CDH, Hortonworks HDP, and MapR. Teradata provides documentation and guidance for configuring TDCH with different Hadoop distributions.

11. Teradata Appliance Integration: TDCH can be used with Teradata appliances, such as Teradata Aster, to extend the analytical capabilities of Teradata into Hadoop.