Google Cloud Dataflow vs Twister2

Overview

Google Cloud Dataflow

Stacks219

Followers497

Votes19

Twister2

Stacks0

Followers1

Votes0

GitHub Stars11

Forks1

Google Cloud Dataflow vs Twister2: What are the differences?

Google Cloud Dataflow: A fully-managed cloud service and programming model for batch and streaming big data processing. Google Cloud Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization; Twister2: Flexible, High performance data processing. It is a high-performance data processing framework with capabilities to handle streaming and batch data. It can leverage high-performance clusters as well we cloud services to efficiently process data.

Google Cloud Dataflow and Twister2 belong to "Real-time Data Processing" category of the tech stack.

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Manual

Detailed Comparison

Google Cloud Dataflow	Twister2
Google Cloud Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.	It is a high-performance data processing framework with capabilities to handle streaming and batch data. It can leverage high-performance clusters as well we cloud services to efficiently process data.
Fully managed; Combines batch and streaming with a single API; High performance with automatic workload rebalancing Open source SDK;	Batch data processing; Streaming data processing
Statistics
GitHub Stars -	GitHub Stars 11
GitHub Forks -	GitHub Forks 1
Stacks 219	Stacks 0
Followers 497	Followers 1
Votes 19	Votes 0
Pros & Cons
Pros 7 Unified batch and stream processing 5 Autoscaling 4 Fully managed 3 Throughput Transparency	No community feedback yet
Integrations
No integrations available	Python Apache Beam

What are some alternatives to Google Cloud Dataflow, Twister2?

Amazon Kinesis

Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.

Amazon Kinesis Firehose

Amazon Kinesis Firehose is the easiest way to load streaming data into AWS. It can capture and automatically load streaming data into Amazon S3 and Amazon Redshift, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today.