Microservice Data Pipeline product
With the popularization of cloud technology, more and more companies, whether active or passive, have embarked on a journey of digital transformation. In this wave of information revolution, microservices have become an indicator. The so-called digital transformation is the process of cloudification and microservices. However, the problem of "data decoupling and fragmentation management" under the microservice architecture has become more prominent with the deepening of microservices. At the same time, due to long-term corporate culture and technical architecture, many data islands have been created, which has seriously hindered the progress of digital transformation.
The scattered and fragmented data makes it extremely difficult to improve the business process, resulting in poor customer experience and difficult business expansion.
The credibility and quality of the data have declined, which seriously hinders the presentation of the value of the data and makes it difficult to make accurate decisions.
Existing data is not easy to reuse, leading to repeated IT investment and increased application infrastructure investment.
Repeated and inefficient ETL operations consume a lot of manpower and man-hours, resulting in ineffective business construction investment.
Capturing changes in the database of the data source and update to the destination database within milliseconds.
Including Oracle, MySQL, SQLServer, PostgreSQL, Sybase, DB2, MongoDB, Excel, CSV, XML, etc.
Automatically map the relational model to the JSON format during the data copy process.
Standardize data rules, while monitoring and analyzing the quality of data obtained.
Provide load balancing, disaster recovery, API usage and traffic management.
Support structured, semi-structured and unstructured data.
Gravity's use case