Summing Bird

Streaming MapReduce with Scalding and Storm.

DecliningOpen SourceLow lock-in

Pricing

Free tier

Flat rate

Adoption

Cooling

License

Open Source

Data freshness

Aging · Jun 8, 2026

Overview

What is Summing Bird?

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.

Key differentiator

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.

Capability profile

Capability Radar

Ease of StartEcosystemValueMaturityFlexibilityScale Ready

Honest assessment

Strengths & Weaknesses

↑ Strengths

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

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

Simplifies the development of complex data pipelines.medium

↓ Weaknesses

Limited language supporthigh

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

Complex setup and configurationmedium

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

Small community and limited third-party supporthigh

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.

Performance issues with large-scale data processingmedium

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.

Fit analysis

Who is it for?

✓ Best for

Developers who need to process large volumes of streaming data in real time.

Teams that require a unified API for both batch and stream processing.

Projects where data consistency between batch and stream processing is critical.

✕ Not a fit for

Applications requiring sub-second latency as Summingbird may not meet such strict requirements.

Use cases needing direct integration with cloud services, as it primarily supports self-hosted environments.

Cost structure

Pricing

Free Tier

Available

Open source — free to use

Starts at

$0

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Next step

Get Started with Summing Bird

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →