AgentIndex icon
AgentIndex
asya logo
asya
★ 59
vs
wanaku logo
wanaku
★ 134

asya vs wanaku

asya: Asya is a queue-based actor framework designed for orchestrating AI/ML workloads on Kubernetes, enabling independent scaling and dynamic pipelines. It allows data scientists to write pure Python functions while handling queues, routing, scaling, and monitoring with zero infrastructure code.; wanaku: Wanaku is an MCP Router designed for AI-enabled applications, standardizing how applications provide context to LLMs. It acts as a centralized routing and resource management system, offering extensive connectivity and secure, Kubernetes-native deployments.

01

TL;DR

asya logo
asyaVision / Multimodal · ★ 59

Multi-step AI/ML pipelines (e.g., document processing, image pipelines, LLM workflows).

Read asya full review →
wanaku logo
wanakuVision / Multimodal · ★ 134

Centralized management and routing of AI agents and resources across various applications.

Read wanaku full review →
02

Side-by-Side Comparison

Field
asya logoasya
wanaku logowanaku
Category
Vision / Multimodal
Vision / Multimodal
Stars
★ 59
★ 134
License
Apache-2.0
Apache-2.0
Install Command
helm install asya deliveryhero/asya --namespace asya-system --create-namespace
jbang app install wanaku@wanaku-ai/wanaku
Updated
1mo ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Actor Framework, Kubernetes, AI/ML Orchestration
AI Router, MCP Protocol, API Gateway
03

Features

asya logoasya
01Independent scaling: Each actor scales 0→N based on its own queue depth.
02Zero infrastructure code: Write pure Python functions without dependencies for queues, routing, or retries.
03Dynamic pipelines: Routes are data, not code, allowing modification at runtime.
04Cost efficiency: KEDA autoscaling from zero to max, paying only for active processing.
wanaku logowanaku
01Unified Access: Centralized routing and resource management for AI agents
02MCP-to-MCP Bridge: Act as a gateway or proxy for other MCP servers
03Extensive Connectivity: Leverage 300+ Apache Camel components for integration
04Secure by Default: Built-in authentication and authorization via Keycloak
05Kubernetes-Native: First-class support for OpenShift and Kubernetes deployments
04

Use Cases

asya logoasya
↳Multi-step AI/ML pipelines (e.g., document processing, image pipelines, LLM workflows).
↳Event-driven workloads (e.g., webhook processing, batch predictions, async API backends).
↳Cost-sensitive deployments (e.g., GPU inference, bursty traffic, dev/staging environments).
wanaku logowanaku
↳Centralized management and routing of AI agents and resources across various applications.
↳Building secure gateways for AI-enabled applications adhering to the Model Context Protocol.
↳Integrating diverse enterprise systems and data sources with AI applications using Apache Camel components.
↳Deploying scalable and secure AI routing infrastructure natively on Kubernetes or OpenShift.
↳Standardizing context provision from applications to Large Language Models (LLMs).
FAQ

FAQ

What is the difference between asya and wanaku?
Both asya and wanaku are in the Vision / Multimodal category. asya has 59 stars, while wanaku has 134 stars.
Which is better, asya or wanaku?
The best choice depends on your use case. Choose asya if Multi-step AI/ML pipelines (e.g., document processing, image pipelines, LLM workflows)., and wanaku if Centralized management and routing of AI agents and resources across various applications..
Is asya free or open source?
Yes, asya is open source on GitHub (Apache-2.0).
Is wanaku free or open source?
Yes, wanaku is open source on GitHub (Apache-2.0).
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Alternatives to asya →Alternatives to wanaku →asya details →wanaku details →