University of California Berkeley’s RISELab is working on a new open source project called Ray that could offer an alternative to Spark. Ray is a distributed, low-latency, real-time processing framework that aims to be faster than Spark.
Ray is based on Python and uses a Redis server to keep track of system state. It is meant to be used for machine learning use cases. It is currently a pre-alpha release.