* Trifacta (http://www.trifacta.com/) are dealing with the very grungy problem of data transformation. Their approach is heavily UX-centric, with built-in predictive capabilities that learn what you are doing as you try to transform disparate data sets to meet your needs.
* Segment (http://www.segment.com) acts as a data router, allowing you to implement significantly less data plumbing in your application while allowing you to deliver your data to many different analytics tools.
* Jut (http://www.jut.io) is a full-stack approach to building a hub for streaming data. They take any operations data (logs, metrics, alerts, events) as inputs, manage storage and analysis, and have creating a framework for streaming visualizations as well. Technologies include an in-browser, retargetable compiler, a streaming analytics layer, storage (elastic search and cassandra), A d3-based visualization framework designed for 3rd party add-ons, and a simpler way to manage large-scale data called hybrid SaaS. (disclosure: I work here.)
* Databricks (http://www.databricks.com) has implemented apache Spark as a service.