Open-source alternatives to Datahub

dbt-core is a command-line framework for transforming data within a warehouse using modular SQL and version control. It functions as a data transformation engine that enables users to define data structures and business logic through declarative configuration files, which the system then compiles into executable code. By managing complex data dependencies through a directed acyclic graph, it ensures that transformation tasks execute in the correct order while maintaining a manifest-driven state to track lineage and execution history. The project distinguishes itself through an adapter-based d

CKAN is an open-source data management platform that provides the foundation for building data portals. It supports the full lifecycle of datasets—from creation and organization to publishing, cataloging with faceted search, and interactive data visualization—all through a web interface. The platform is built on a modular architecture that includes a plugin-based extensibility system, a harvesting framework for importing metadata from external sources, and a standardized RESTful JSON API for programmatic access to datasets and metadata. The web interface is rendered using the Jinja2 templatin

Gravitino is a federated metadata lake and unified data catalog designed to manage tables, files, and AI models across diverse data sources and cloud storage. It serves as a centralized interface for governing schemas, access controls, and tagging across relational databases, messaging queues, and object stores. The project distinguishes itself by unifying the management of AI assets, such as machine learning models and their version lineages, alongside traditional tabular data. It also implements the Iceberg REST specification to provide a standardized metadata server and proxy for lakehouse

Prefect is a workflow orchestration platform designed to define, schedule, and monitor complex data pipelines as Python code. It functions as a container-native engine that wraps individual tasks in isolated environments, ensuring consistent dependencies and resource allocation across diverse infrastructure. By utilizing a state-machine-based orchestration model, the system tracks execution progress through discrete transitions and persistent event logs to maintain reliable and observable task processing. The platform distinguishes itself through a decoupled worker-API architecture, which sep

Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma

Dagster is a data orchestration platform designed to manage the entire lifecycle of data assets through declarative modeling and version-controlled code. It functions as a workflow engine that treats data assets as first-class primitives, allowing teams to define, schedule, and monitor complex pipelines while maintaining clear visibility into lineage, dependencies, and data quality. The platform distinguishes itself by using a code-as-configuration framework that enables standard software engineering practices, such as unit testing and local mocking, to be applied directly to data workflows.

Rudder Server is a customer data platform and event routing pipeline designed to collect, transform, and route customer event data from various sources to data warehouses and business tools. It functions as a customer identity resolver, linking identifiers from multiple sources to build a unified identity graph and comprehensive behavioral customer profiles. The system differentiates itself through reverse ETL capabilities, which push processed customer segments and audiences from data warehouses back into operational third-party applications. It also provides a containerized data plane for K

This project is an exploratory data analysis framework and profiling tool designed to generate comprehensive statistical reports from Pandas and Spark DataFrames. It functions as a data quality profiler that identifies missing values, duplicates, and high correlations within tabular datasets. The tool distinguishes itself through specialized capabilities for time-series analysis, extracting temporal statistics, seasonality, and auto-correlation plots. It also includes a dataset comparison utility to identify structural or content changes between different versions of a dataset. The analysis

aws-sdk-pandas is a Python library that integrates pandas dataframes with AWS services, acting as a cloud data ETL tool and data lake connector. It provides a unified interface to move and transform data between in-memory dataframes and cloud storage, databases, and data warehouses. The project distinguishes itself as a distributed compute orchestrator capable of submitting pandas-based workloads to EMR clusters and serverless processing environments. It further specializes in coordinating distributed data processing via Ray cluster initialization to handle datasets that exceed the memory of

A federated, open-source data catalog for all your big data and small data

OpenTSDB is a distributed time series database and metrics engine designed for storing and managing massive volumes of high-cardinality system metrics. It functions as a data store and analytics platform that enables large-scale metric ingestion and infrastructure performance monitoring across a distributed cluster. The system distinguishes itself through a distributed storage abstraction that supports multiple backends such as HBase, Cassandra, and Google Bigtable. It utilizes a hierarchical metric tree to organize time series and employs numeric identifier indexing to reduce storage footpri

DevLake is a DevOps data platform and analytics tool designed to orchestrate data pipelines that ingest, transform, and sync metadata from external development tools into a unified database. It functions as a system for collecting and normalizing data from source control, CI/CD pipelines, and issue trackers into a standardized schema to enable consistent software delivery analytics. The platform distinguishes itself by transforming tool-specific data into a common domain model, allowing for the calculation of engineering metrics via SQL. It provides specialized frameworks for measuring DORA m

Evidently is an AI observability platform and evaluation framework designed to quantify the performance of machine learning models and large language models. It functions as a monitoring tool for detecting data drift and quality degradation in tabular datasets, while providing a specialized analyzer for the faithfulness and correctness of retrieval augmented generation systems. The project distinguishes itself through an evaluation framework that utilizes judge models and custom rubrics to score language model outputs. It includes tools for iterative prompt optimization and the generation of

Kùzu is an embedded property graph database engine designed for high-performance analytical queries and local data management. It operates as a library within the host application process, utilizing a columnar-based storage architecture and just-in-time query compilation to execute complex graph traversals and pattern matching efficiently. By mapping database files directly into system memory, it ensures data durability and high-speed access while maintaining ACID-compliant transactional integrity. The engine distinguishes itself by integrating vector similarity search and full-text search di

unopim is an AI-powered product information management system that serves as a centralized repository for managing product attributes, categories, and variations. It functions as a containerized product repository and a multi-channel data distributor, synchronizing consistent product information and pricing across diverse external sales platforms and marketplaces. The platform distinguishes itself through an LLM-based catalog manager that provides a conversational interface for executing data management tasks. This allows users to perform item creation, content enrichment, and quality scans u

Subfinder is a security reconnaissance framework designed for subdomain enumeration and attack surface management. It functions as a discovery engine that identifies and maps internet-exposed infrastructure, cloud-hosted assets, and network ranges to maintain a comprehensive inventory of an organization's digital footprint. The project distinguishes itself through a modular, template-driven scanning engine that executes security checks against discovered assets. It leverages cloud-native asset discovery to query provider APIs and infrastructure metadata, while supporting distributed agent orc

Ludwig is a declarative machine learning framework designed for training neural networks and large language models using configuration files instead of manual coding. It functions as a multimodal model builder and a low-code tool for supervised fine-tuning, allowing users to build models that process mixed inputs of text, images, audio, and tabular data. The project distinguishes itself through an automated hyperparameter optimizer and a system for large language model fine-tuning using parameter-efficient adapters. It features a multimodal data pipeline and the ability to automatically gener

Kedro is a data science pipeline framework and orchestration tool designed to build reproducible and modular data engineering workflows. It functions as an MLOps project template and Python data workflow tool that enforces software engineering best practices to move projects from prototype to production. The system distinguishes itself through a centralized data catalog manager that abstracts data access and versioning across various file formats and cloud storage systems. It further separates processing logic from data access via a lazy-loading data registry and provides a standardized proje

Vizro is a low-code Python framework for building production-ready data visualization applications. It functions as a UI orchestrator that allows users to define multi-page analytical dashboards through structured configurations in Python, YAML, or JSON, reducing the need for extensive frontend engineering. The project distinguishes itself through generative AI integration, utilizing a model context protocol server to translate natural language descriptions into validated dashboard configurations, charts, and layouts. It also features a decoupled data cataloging system that separates data sou

Kedro is a data science pipeline framework and production toolbox designed to build reproducible, modular workflows using software engineering best practices. It functions as a data engineering orchestrator and catalog manager, bridging the gap between interactive analysis and maintainable production pipelines. The framework distinguishes itself by using a data catalog to decouple data access from processing logic and providing tools to transition analysis from interactive notebooks into structured workflows. It includes a workflow visualization tool that generates visual maps of data pipelin

Harlequin is a terminal-based SQL IDE that runs queries against DuckDB and SQLite databases, with a plug-in adapter system for connecting to additional database engines. It provides a full-screen text editor with syntax highlighting and fuzzy autocomplete for writing SQL, and displays query results in a scrollable table within the terminal. The application distinguishes itself through a tree-based data catalog that lets you browse database schemas, local files, and remote S3 objects, with the ability to insert or copy paths directly into the query editor. It supports custom key bindings throu

This project is an AWS pandas integration library and data pipeline framework designed to simplify the movement and transformation of data between local memory and AWS storage and analytics services. It functions as a cloud data lake toolkit and storage file manager, allowing users to read, write, and transform structured data across various cloud environments. The library distinguishes itself as a distributed compute orchestrator capable of managing clusters in environments such as EMR to process datasets that exceed the memory limits of a single machine. It also provides specialized capabil

Vanna is a Python framework designed to build conversational interfaces that translate natural language into executable database queries. It functions as an enterprise-grade toolkit that connects language models to relational databases, allowing users to retrieve information through conversational prompts rather than manual code. The system maintains context across interactions by utilizing vector databases to store historical query patterns and schema metadata. The framework distinguishes itself through a focus on security and schema-aware generation. It incorporates granular access control,

Cocoindex is an incremental data processing engine that builds and maintains live indexes for AI agents, with a core focus on codebase indexing and knowledge graph extraction. The engine uses a function-graph execution model where user-defined Python functions are composed into a directed acyclic graph, and it processes data incrementally so only changed source records or code paths are re-computed, avoiding full recomputation at any scale. It supports automatic schema inference from transformation pipeline type annotations and provides full data lineage tracing, tagging every output record wi

Airweave is a unified AI knowledge base platform that syncs data from external APIs into a searchable layer for retrieval-augmented generation. It provides a pre-built data connector library and a framework for building custom connectors, enabling the extraction, transformation, and synchronization of structured and unstructured data from SaaS applications. The platform includes a hybrid vector retrieval system that combines semantic, neural, and keyword search strategies to deliver grounded context for AI agents. The platform distinguishes itself through an agentic search engine that iterati

sqlglot is a SQL parser and transpiler that represents queries as abstract syntax trees to enable structural analysis, modification, and semantic transformation. It functions as a dialect translator and query optimizer, converting SQL code between different database engines and simplifying syntax trees through rule-based normalization. The project provides a framework for defining custom SQL dialects by overriding tokenizers, parsers, and generators. It includes a lineage analyzer to track data flow from source tables through complex queries to identify the origin of specific columns. Additi

Polyaxon is a Kubernetes-native machine learning orchestration platform and MLOps pipeline orchestrator. It serves as a control plane for managing distributed deep learning workloads, automated machine learning pipelines, and experiment tracking. The platform distinguishes itself through specialized services for distributed training management, including MPI-based coordination for PyTorch and TensorFlow. It provides an automated hyperparameter optimization service utilizing Bayesian, random, and grid search algorithms, alongside managed interactive AI workspaces for launching Jupyter notebook