Would it be possible to add Flink and Spark Connector?
As Dgraph supports real-time updates, it make sense to enable real time push down update from analytics / ETL engine such as Spark and/and Flink.
Flink has got integrated push down connector to RocksDB already.
Data flow model:
Kafka -> Flink -> Dgraph
Once data is enriched through Flink in real time, it would be updating existing graph in Dgraph. And if required data will be lifted entirely to flink/spark for MLib.
Imagine collecting live signals from mobile phones inc: lat,long,user_id,TS. Then transforming each log into geoCity,GeoCountry, Date/TOD/DOW, gender, interests while matching each log with static tables in Flink, then updating Graph as the data comes through so that user has a low latency access to live data.
I am happy to contribute if you can point me to a right direction.