I wasn't aware of an export feature. As long as the export comes in a reasonable machine readable format that should be equally fine and would remove the need for access to RDB files for my use case.
Use case for RDB backups: for rather large redis datasets (>50GB) with long living keys (90days and beyond) I found it useful to be able to parse an RDB snapshot using the python rdbtools and iterate over the whole dataset, e.g. in order to migrate data to a different format. I found this usually more stable and reliable than using SCAN and the likes.
mbr targeting / Ströer Digital Group | Berlin | Full-Time | On-Site | Big Data Engineer
At mbr targeting in Berlin we are developping and scaling the core technology that powers Germany's market leading digital advertising company Ströer.
With online advertising being one of the most challenging fields in high performance computing and data processing, we are working at the cutting edge of big data, machine learning and real-time technologies and we are operating large-scale deployments of real-time web services.
To expand our team of highly skilled engineers we are looking for talented engineers who either already have some experience with big data technologies or who are willing to expand their skillset into the area of these technologies.
The languages we're speaking are Java, Scala and Python (if you're fluent in one of them that's fine!) and technology buzzwords include Hadoop, Spark, Flink, Storm, Hive, Impala, Kafka, Druid, …