TigerGraph: A Native MPP Graph Database
Not on the map. Why?
Abstract (arXiv)
We present TigerGraph, a graph database system built from the ground up to support massively parallel computation of queries and analytics. TigerGraph's high-level query language, GSQL, is designed for compatibility with SQL, while simultaneously allowing NoSQL programmers to continue thinking in Bulk-Synchronous Processing (BSP) terms and reap the benefits of high-level specification. GSQL is sufficiently high-level to allow declarative SQL-style programming, yet sufficiently expressive to concisely specify the sophisticated iterative algorithms required by modern graph analytics and traditionally coded in general-purpose programming languages like C++ and Java. We report very strong scale-up and scale-out performance over a benchmark we published on GitHub for full reproducibility.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Jan 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 1; 2025: 1; 2026: 1.
6 papers.
- 2022Distributed Graph Neural Network Training: A Surveycited by 32
- 2025Top Ten Challenges Towards Agentic Neural Graph Databasescited by 13
- 2024Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batchcited by 10
- 2023Knowledge Graphs Queryingcited by 5
- 2021ProGS: Property Graph Shapes Language (Extended Version)cited by 1
- 2026LogosKG: Hardware-Optimized Scalable and Interpretable Knowledge Graph Retrievalcited by 0
- 2026LogosKG: Hardware-Optimized Scalable and Interpretable Knowledge Graph Retrieval20 Apr 2026
- 2025Top Ten Challenges Towards Agentic Neural Graph Databases24 Jan 2025
- 2024Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch1 Jun 2024
- 2023Knowledge Graphs Querying23 May 2023
- 2022Distributed Graph Neural Network Training: A Survey1 Nov 2022
- 2021ProGS: Property Graph Shapes Language (Extended Version)12 Jul 2021