Google Cloud Memorystore vs Kafka

Written at LinkedIn in Scala;Used by LinkedIn to offload processing of all page and other views;Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled);Supports both on-line as off-line processing

Less DevOps, More Code - Spend more time writing code that takes advantage of the power of Redis and less time managing Redis. Cloud Memorystore automates complex tasks like enabling high availability, failover, patching, and monitoring so that you can spend more time coding.; Scale as Needed - With Cloud Memorystore for Redis, you can easily achieve the sub-millisecond latency and throughput your applications need. Start with the lowest tier and smallest size, and then grow your Redis instance effortlessly with minimal impact to application availability. Cloud Memorystore can support instances up to 300 GB and network throughput of 12 Gbps.; Highly Available - High availability instances are replicated across two zones and provide a 99.9% availability SLA (when generally available). Instances are monitored constantly, and with automatic failover, applications experience minimal disruption.; Google Grade Security - Cloud Memorystore instances are isolated and protected from the internet using private IPs and are further secured using IAM role-based access control.; Easy Lift and Shift - Cloud Memorystore for Redis is Redis protocol compatible. You can lift and shift your applications from open source Redis to Cloud Memorystore without any code changes. There is no need to learn new tools since all existing tools and client libraries just work.