Description.
We're not just focused on speeding up the application build process, we're focused on helping you achieve your ultimate goal - to make your applications run efficiently. Therefore, we are pleased to announce the release of Redis Data Integration (RDI).
RDI is a tool designed to enable real-time data synchronization to Redis, reducing the burden of building custom data pipelines. With RDI, you can efficiently convert traditionally slow data into high-speed data, enabling unlimited scalability and reducing database-related costs. Best of all, all this is possible without having to write additional code.
Break the bottleneck of database performance and scalability to build efficient and scalable applications. RDI allows you to leverage your existing databases while seamlessly accessing the high-speed features of Redis to achieve superior performance for modern applications.
RDI creates a data stream pipeline that can mirror data from existing databases to Redis. as a direct result of this -- the The application can access the original data at a very high speed.
By seamlessly integrating slow databases with Redis, RDI enables data ingestion and conversion to the Redis format, which dramatically improves data access speeds.
Once your application is plugged into Redis, you'll have fast access to the data you need. You can also do real-time queries directly in Redis, as the complete dataset is converted to the format your application needs.
RDI simplifies the process of building rapid applications by maintaining profiles for synchronization rather than code synchronization.In this way, you can avoid consuming resources by manually building data pipelines that capture, ingest, and convert changed data from your database to Redis. By automating configuration, RDI ensures that data is seamlessly synchronized, keeping Redis in sync with your database. To further simplify management, you will soon be able to manipulate and visualize your data pipeline through Redis Insight, the official visual interactive desktop client, and RDI.
Combining RDI and Redis Insight simplifies the pipeline creation process - seamlessly deploying pipelines in Redis Insight, performing code completion and grammar validation, validating transformations and pipeline outputs, and monitoring data flow and pipeline performance in an intuitive dashboard.
RDI provides a new way for organizations that want to modernize their applications but are faced with high database costs. Often, the modernization process involves the spread of duplication and expensive licensing fees.
Now, with RDI, you can offload the task of reading data to Redis without the expensive cost of a read copy, making it a more cost-effective way to access data quickly and reliably. This means you can deliver predictable, high-speed data to multiple microservices and applications that need real-time data.
Say goodbye to the days of spending development time building data pipelines or spending huge amounts of money on third-party business data integration tools!
Axis Bank Limited is a premier Indian multinational banking and financial services organization headquartered in Mumbai. Being India's third largest private bank in terms of assets and fourth largest in terms of market capitalization, Axis Bank offers a wide range of financial services to a wide customer base.
Axis Bank's mobile application was designed to allow users to view all up-to-date account information, including the products and services they use and the people authorized to access their accounts. However, when customers made these changes offline at the branch, the changes were not immediately reflected in the application - this was because the infrastructure at the time was based on a traditional relational database. Naturally, theThis lack of reliable, real-time data led to customer complaints and dissatisfaction with the user experience.
To solve this problem, they decided to use Redis to read data from the mobile application, but still needed a simple way to synchronize the data in the main database.With RDI, Axis Bank can easily import relevant records into Redis without the need for complex code or expensive ETL tools.They can immediately capture and process real-time changes to data in nine large master database tables. This means they can provide a 4.25 times faster response time compared to retrieving data directly from core bank tables - a huge leap in system performance and overall efficiency.
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