NeuG is a high-performance embedded graph database designed for both analytics and real-time transactional workloads. It is built to be lightweight and embeddable, allowing integration directly into Python applications as a single binary with minimal external dependencies. NeuG can operate in two distinct modes: embedded mode for offline analytics and service mode for online, concurrent transactions. This dual-mode flexibility addresses the needs of data science workflows, machine learning pipelines, research prototyping, as well as production applications requiring real-time recommendations or anti-fraud systems.
The database supports industry-standard Cypher queries and is described as GQL-ready, leveraging GOpt’s unified intermediate representation for compatibility with emerging ISO/GQL standards. NeuG features an extensible architecture inspired by Postgres and DuckDB, enabling users to keep the core system lean while adding graph algorithms, vector search, or custom procedures as needed. The platform has demonstrated performance exceeding 80,000 queries per second and is built on GraphScope Flex, which has achieved top results on the LDBC SNB Interactive benchmark using Cypher queries.
NeuG’s embedded mode is tailored for analytics, supporting batch data loading, ETL processes, complex pattern matching, and full-graph algorithms. It is suitable for use cases such as Jupyter notebooks, offline analytics, and graph machine learning feature extraction. In service mode, NeuG provides a network service capable of concurrent read-write operations, low-latency point queries, multi-session ACID transactions, and is intended for web or mobile backends where real-time data processing is required.
8+ on Linux and macOS (x86 and ARM architectures). 0 license. js client, support for graph algorithms like Leiden community detection, and data lake integration with S3/OSS and Parquet. NeuG is positioned as a versatile solution for developers building graph-based applications across a range of analytical and transactional scenarios.
NeuG sits in PulseGate's Databases (SQL, NoSQL, vector, graph) category. It enables developers and data scientists to embed high-performance graph analytics and transactional storage into Python applications. It is built as an open-source project for developers and data scientists. NeuG is open source under the Apache-2.0 license. It runs on the web, the command line, and embeddable surfaces, and it can be self-hosted.
NeuG first shipped in 2026. Development happens publicly on GitHub with 118 stars and 183 commits in the last 90 days. Key capabilities include embedded database, cypher query support, and extensible framework.
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