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What is OllaCoder?

OllaCoder acts as a private AI coding assistant designed for integration with VS Code, specifically aimed at developers who wish to keep their source code off external servers. Functioning locally, it leverages your personal Ollama models and includes features like agent mode, inline edits, codebase chat, smart autocomplete, MCP servers, and a local-first runtime, all accessible within a unified editor environment. At the heart of OllaCoder's philosophy is the belief that software development is an inherently personal task, emphasizing that your code should be kept under your control while offering a reliable, transparent, and non-intrusive AI assistant. It primarily interacts with your local Ollama instance, ensuring that all prompts, completions, and adjustments stay on your device; utilizing cloud services remains optional, and API keys are securely managed within the OS keychain. The agent mode functionality allows for task planning, file modifications, terminal command executions, and verification of its outputs, enabling users to approve, deny, or undo any actions performed. Furthermore, the inline edits capability allows users to choose a function, outline the needed change, and view a detailed diff, thereby enhancing the overall coding experience. With its focus on code privacy and robust AI-assisted development tools, OllaCoder marks a crucial advancement in the realm of software development, fostering an environment where developers can innovate freely while maintaining control over their work. This innovative approach not only streamlines the coding process but also reassures developers about the safety of their intellectual property.

What is Azkaban?

Azkaban is a distributed workflow management system created by LinkedIn to tackle the challenges related to Hadoop job dependencies. We encountered situations where jobs needed to run in a specific order, which spanned various applications from ETL processes to data analytics. Following the launch of version 3.0, we established two operational configurations: the standalone "solo-server" mode and the distributed multi-executor mode. The upcoming sections will clarify the differences between these two modes. In the solo server mode, the system utilizes the embedded H2 database, and both the web server and executor server run within the same process, making it suitable for small-scale applications or experimentation. In contrast, the multiple executor mode is designed for more serious production scenarios and necessitates a more sophisticated configuration with a MySQL database set up in a master-slave structure. To improve user experience, it is advisable for the web server and executor servers to operate on different hosts, which helps ensure that upgrades and maintenance do not interfere with service continuity. This architectural choice not only boosts the scalability of Azkaban but also enhances its resilience and efficiency when managing intricate workflows. Ultimately, these operational modes provide flexibility to users while meeting a variety of workflow demands.

Media

Media

Integrations Supported

DeepSeek
Groq
Mistral AI
Model Context Protocol (MCP)
Ollama
OpenAI
OpenRouter
Together AI
Visual Studio Code

Integrations Supported

Hadoop
IBM watsonx.data integration
MySQL

API Availability

Has API

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided

Supported Platforms

Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

OllaCoder

Company Location

United States

Company Website

ollacoder.com

Company Facts

Organization Name

Azkaban

Company Website

azkaban.github.io

Categories and Features

AI Coding Assistants

Not specified

Categories and Features

Data Pipeline

Not specified

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