Summing Bird

What it is

Summingbird is a framework for streaming MapReduce that allows developers to write jobs in Scala, which can run on either Apache Storm or Hadoop's MapReduce. It simplifies the process of writing real-time data processing applications by providing a unified API.

Summingbird stands out by providing a unified API for both batch and stream processing, allowing developers to write jobs that can run on either Apache Storm or Hadoop's MapReduce without changing the codebase.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited language support

   Summingbird primarily supports Scala, which may restrict usage for teams not proficient in this language.

2. 02

   Complex setup and configuration

   Setting up Summingbird requires a deep understanding of both Apache Storm and Hadoop's MapReduce, leading to a complex deployment process.

3. 03

   Small community and limited third-party support

   The open-source nature of Summingbird leads to a smaller user base and fewer contributions compared to larger frameworks like Apache Kafka or Spark Streaming, which can limit the availability of plugins and integrations.

4. 04

   Performance issues with large-scale data processing

   Summingbird may experience performance bottlenecks when handling very large datasets due to its reliance on Scala for both real-time and batch processing, which can be less efficient than specialized frameworks.

What it does well

• Unified API for both batch and real-time processing.

• Supports running jobs on Apache Storm or Hadoop's MapReduce.

• Simplifies the development of complex data pipelines.

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.