Giskard provides open source evaluation and testing tools for LLM agents.
The Best DB GPT Alternatives in 2026
Looking for something like DB GPT? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 21 are open source.
DB-GPT is an open-source agentic data assistant for AI and data products.
Top picks at a glance
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Giskard | — | Yes | — |
| 2 | Open-RAG-Eval | — | Yes | — |
| 3 | Vearch | — | Yes | — |
| 4 | opendatalab/MinerU | — | Not stated | — |
| 5 | RagTune | — | Yes | — |
| 6 | AutoRAG | — | Not stated | — |
| 7 | LLM Evaluation Metrics: Everything You Need for LLM Evaluation - Confident AI | — | Not stated | Web |
| 8 | Adala | — | Yes | — |
| 9 | pytorch tabular | — | Yes | — |
| 10 | PyTorch Frame | — | Yes | — |
All DB GPT alternatives
Open-RAG-Eval evaluates retrieval-augmented generation without requiring golden answers.
Vearch provides distributed vector search capabilities for applications built around artificial intelligence.
opendatalab/MinerU
github.com/opendatalab/MinerUMinerU converts complex PDF and Office documents into Markdown or JSON for AI workflows.
RagTune helps inspect, debug, benchmark, and tune retrieval for retrieval augmented generation systems.
AutoRAG
github.com/Marker-Inc-Korea/AutoRAGAutoRAG helps an agent search for information across files on a computer.
LLM Evaluation Metrics: Everything You Need for LLM Evaluation - Confident AI
confident-ai.com/blog/llm-evaluation-metrics-e…This guide explains LLM evaluation metrics, including measures for retrieval augmented generation and agents, with DeepEval examples.
Adala automates data labeling through an autonomous agent framework for organizing labeled datasets.
pytorch tabular provides a unified framework for deep learning models on tabular data.
PyTorch Frame provides a library for applying deep learning models to tabular data.
tsfresh automatically extracts relevant features from time series data.
Snorkel helps generate training data programmatically through weak supervision.
Apache Spark is a unified engine for large-scale data processing and analytics.
Disco’s discovery engine finds statistically validated patterns in tabular data, including feature interactions and subgroup effects.
ADAM analyzes genomics data with specialized file formats built on Apache Spark, Avro, and Parquet.
Modin scales Pandas data workflows by changing a single line of code in a project.
This TabGAN repository reviews research on applying GANs to generate tabular data.
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
NALP covers Natural Adversarial Language Processing through a dedicated library.
neuropredict evaluates predictive performance using neuroimaging features.
Cornac provides a framework for comparing multimodal recommender systems and recommendation algorithms.
nilearn provides Python tools for machine learning and neuroimaging analysis.
This repository implements YOLOv3 variants in PyTorch for real time object detection, training, validation, inference, and export.
Captum explains model behavior and supports interpretability analysis for PyTorch systems.
Alternatives to similar tools
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