Different Type of Data Integration Tools People Use
Published: 2023-11-10 15:53:54

Data integration technology has rapidly iterated along with the development of the big data technology stack. It has evolved from early offline data integration to gradually include real-time data integration, giving rise to an increasing number of excellent products.
## **_Offline BigData Integration_**  
### SQOOP
Apache SQOOP is a specialized tool that facilitates seamless data transfer between HDFS and various structured data repositories. These repositories could include relational databases, enterprise data warehouses, and NoSQL systems. SQOOP operates through a connector architecture, which employs plugins to enhance data connections with external systems, ensuring efficient data migration. 

![sqoop](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/mstrw3fov7gh0nzy4uls.png)

### Datax
DataX is a widely used offline data synchronization tool/platform within Alibaba, which practically achieves the extension of all common data storage. It supports data synchronization between various heterogeneous data sources. DataX, as an offline data synchronization framework, adopts a Framework + plugin architecture. It abstracts data source reading and writing into Reader/Writer plugins, incorporating them into the entire synchronization framework.

![datax](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/07b16hute1jysqzur8jv.png)

## **_Real-time incremental data integration_**
### Canal

Its primary purpose is based on parsing incremental logs from MySQL databases, providing incremental data subscription and consumption. Currently, it supports MySQL versions including 5.1.x, 5.5.x, 5.6.x, 5.7.x, and 8.0.x.

![canal](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/2cbyl85aykhyygf6km93.png)

### FlinkCDC
In traditional CDC-based ETL analysis, the process involves first collecting data, then relying on an external message queue (MQ) for data delivery, performing calculations after downstream consumption, and finally storing the data. The overall data pipeline is relatively long. The core concept of FlinkCDC is to simplify the data pipeline by integrating Debezium for binlog collection at the lower level, eliminating the need for an MQ, and ultimately performing calculations through Flink. The entire pipeline is based on the Flink ecosystem, providing a clearer structure.

![flinkcdc](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/lzj05pc6xux4dqy25jm1.png)

##  **_New Real-time data integration_**

### Airbyte
Airbyte is an open-source data integration engine that enables the rapid construction of a reliable data pipeline (supporting Change Data Capture - CDC) in a matter of minutes. It facilitates integration and synchronization from source to destination, encompassing data from databases, data warehouses, and data lakes. Airbyte, grounded in a modern understanding of Extract, Load, and focusing on the Extract and Load phases, delegates transformation operations to dbt. Its robust open-source ecosystem supports 200+ connectors, with ongoing additions according to the product development roadmap.

![airbytes](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/hcn66lpg7e13n63z7ce6.png)

### Fivetran

Fivetran connects to all of your supported data sources and loads the data from them into your destination. Each data source has one or more connectors that run as independent processes that persist for the duration of one update. 

![fivetrans](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/jm21y0j2kmrenyevz34n.png)

There are many different eras of big data integration products, including **Debezium, Maxwell, Flinkx, SeaTunnel, Stitch, Singer, Meltano**, there is no absolute 'best' option; it depends on specific use cases and requirements. Each product has its unique features, applicable scope, and strengths. Users should choose based on their specific data integration needs, technology stack, and preferences.