Google Cloud named a leader in the Forrester Wave: Streaming Analytics
We’re pleased to announce that Forrester has named Google Cloud as a leader in The Forrester Wave™: Streaming Analytics, Q3 2019. We believe the findings reflect Google Cloud’s market momentum, and what we hear from our satisfied enterprise customers who are using Cloud Pub/Sub and Cloud Dataflow in production for streaming analytics in conjunction with our broader platform.
According to Forrester, many leading enterprises realize that real-time analytics—the analytics of what’s happening with data in the present—is an incredible competitive advantage. With it, they can act right away to serve customers, fix operational problems, power internet of things (IoT) apps, and respond decisively to competitors. The report evaluates the top 11 vendors against 26 rigorous criteria for streaming analytics to help enterprise IT teams understand their options and make informed choices for their organizations. Google scored 5 out of 5 in Forrester’s report evaluation criteria of scalability, availability, aggregates, management, security, extensibility, ability to execute, solution roadmap, partners, community, and customer adoption.
How Cloud Pub/Sub and Cloud Dataflow work for usersThere’s a lot of pressure on companies today to become data-driven, but they need high-performing technology to make that a reality. As part of our larger cloud data analytics platform, Cloud Pub/Sub and Cloud Dataflow are designed for ease of use, scalability, and performance. We’re especially pleased that our recognition as a Leader in the Forrester Wave: Streaming Analytics mirrors what we hear from our customers: The report notes that “Google Cloud unifies streaming analytics and batch processing the way it should be. No compromises.” While stream analytics is a leading business priority, real-life use cases frequently require batch data as an input as well. Google Cloud Platform (GCP) customers can simplify their pipeline development by reusing code across both batch and stream processing using Apache Beam, which also provides pipeline portability to OSS projects. Further, Google Cloud’s data analytics portfolio autoscales across ingestion, processing, and analysis, which eliminates the need for provisioning and makes handling varying volumes of streaming data automatic. We hear from users that they’re able to ingest and process data much more quickly than in the past, helping to get new business insights faster and allowing more users to do self-serve analytics.
Cloud Pub/Sub is our stream event ingestion service, which uses a publish/subscribe pattern to deliver events across stream, batch, and unified pipelines. Cloud Pub/Sub is a global service that enables data engineers to automatically scale without provisioning, partitioning, or isolation concerns. We hear that users choose this because it allows them to be production-ready from day one, with end-to-end encryption, virtually unlimited throughput, and high data durability and availability with cross-zone replication. They’re able to access more data faster to find new insights and focus on new projects, not managing infrastructure.
We are very excited about the productivity benefits offered by Cloud Dataflow and Cloud Pub/Sub. It took half a day to rewrite something that had previously taken over six months to build using Apache Spark.
Cloud Dataflow offers simplified stream and batch processing in one service without compromises, which the Forrester report says “must be the goal when software architects create a unified streaming and batch solution that must scale elastically, perform complex operations, and have the resiliency of Rocky Balboa. Google’s Cloud Dataflow is that solution for Google Cloud Platform.” In addition to scaling automatically, Cloud Dataflow is deeply integrated with our other GCP services (including Cloud Pub/Sub, in particular), provides exactly-once processing with built-in fault tolerance, and automates performance, availability, security, and compliance.
Cloud Dataflow’s streaming capabilities allow businesses to capture fleeting opportunities by analyzing real-time events while the window to act on analysis is still open. "Google Cloud Dataflow allowed us to rapidly prototype, iterate, and launch a next-generation platform for analytics at Twitter. It has been able to easily scale to our needs, handling multiple TB of streaming and batch data per hour,” says Steve Niemitz, Staff Software Engineer, Twitter. “Being fully managed by Google allows us to focus on value-add for our users rather than operational issues. Additionally, the ability to write a single job in Beam and then run it in both streaming and batch mode has drastically simplified our codebase and operations."
We’re pleased with our ranking as a Leader in this Wave. However, as the 5/5 evaluation score in the solution roadmap criterion indicates, what we’re most excited about is the opportunity to continue to develop our stream analytics solution to be even more powerful for our customers. Stay tuned as we continue developing new capabilities, expanding the number of ways our customers can drive real value from real-time analytics.