Draft:AgensGraph

AgensGraph uniquely blends SQL and Cypher queries, enabling seamless interaction with both relational and graph data in a single query.

• It supports a multi-model approach, handling property graphs, relational data, and JSON documents, simplifying diverse data management.

• Hierarchical label organization via "Label Inheritance" structures large graph datasets efficiently.

• Property indexing on vertices and edges ensures fast queries, while constraints maintain data integrity.

• It supports relational and graph data triggers.

• ACID transactions guarantee data reliability.

• It support SQL syntax, Cypher syntax and also hybrid of both queries.

AgensGraph's fundamental graph components are nodes, edges that establish connections between nodes, and the properties that characterize each node and edge.

AgensGraph utilizes relational tables to persist graph data.{{cite journal |last1=Bimonte |first1=Sandro |last2=Gallinucci |first2=Enrico |last3=Marcel |first3=Patrick |last4=Rizzi |first4=Stefano |title=Logical design of multi-model data warehouses |journal=Knowledge and Information Systems |date=1 March 2023 |volume=65 |issue=3 |pages=1067–1103 |doi=10.1007/s10115-022-01788-0}} Each node and edge type is represented by a dedicated table. Dynamic node properties are handled through JSON object storage, and B-tree indexes are automatically generated to optimize query performance.{{cite journal |last1=Angles |first1=Renzo |last2=Bonifati |first2=Angela |last3=Dumbrava |first3=Stefania |last4=Fletcher |first4=George |last5=Green |first5=Alastair |last6=Hidders |first6=Jan |last7=Li |first7=Bei |last8=Libkin |first8=Leonid |last9=Marsault |first9=Victor |last10=Martens |first10=Wim |last11=Murlak |first11=Filip |last12=Plantikow |first12=Stefan |last13=Savkovic |first13=Ognjen |last14=Schmidt |first14=Michael |last15=Sequeda |first15=Juan |last16=Staworko |first16=Slawek |last17=Tomaszuk |first17=Dominik |last18=Voigt |first18=Hannes |last19=Vrgoc |first19=Domagoj |last20=Wu |first20=Mingxi |last21=Zivkovic |first21=Dusan |title=PG-Schema: Schemas for Property Graphs |journal=Proc. ACM Manag. Data |date=20 June 2023 |volume=1 |issue=2 |pages=198:1–198:25 |doi=10.1145/3589778}}

AgensGraph boasts comprehensive support for two powerful query languages: SQL and Cypher. This dual-language capability allows users to leverage the strengths of both relational and graph database paradigms.

For relational data manipulation, AgensGraph adheres to standard SQL syntax, ensuring compatibility with existing applications and tools. When navigating complex relationships and patterns within graph data, users can seamlessly switch to Cypher, a declarative graph query language designed for intuitive and efficient traversal.

SELECT p.first_name, p.last_name, ct.name

FROM person p, city c

WHERE nationality(c.name) = 'EU'

AgensGraph's Cypher implementation aligns closely with the openCypher specification, facilitating interoperability and ease of use for developers familiar with other graph databases.

MATCH (p:Person)-[:LIVES_IN]->(c:City), (p:Person)-[:NATIONAL_OF]->(EUCountry)

RETURN p.first_name, p.last_name, c.name, c.state

In AgensGraph you can also write hybrid queries to increase performance, better data integration. There are two ways to write hybrid queries.

1. Cypher in SQL

SELECT p.first_name, p.last_name, ct.name

FROM city c,(MATCH (p:Person) RETURN p) as person,

WHERE nationality(c.name) = 'EU'

2. SQL in Cypher

MATCH (p:Person)

WHERE p.city IN (SELECT city FROM countries WHERE nationality(city) = 'EU')

RETURN properties(p) AS p;

Both ISO standards GQL{{cite web |title=ISO/IEC 39075:2024 |url=https://www.iso.org/standard/76120.html |website=ISO |access-date=17 March 2025 |language=en}} and SQL/PGQ {{cite web |title=ISO/IEC 9075-16:2023 |url=https://www.iso.org/standard/79473.html |website=ISO |access-date=17 March 2025 |language=en}} (Published in 2023 and 2024 respectively) support hybrid query syntax which combines graph and relational model.

In term of transaction processing, complex aggregate queries and data import, AgensGraph is 3x to 25x faster than ArangoDB and OrientDB.{{cite journal |last1=Zhang |first1=Chao |last2=Lu |first2=Jiaheng |title=Holistic evaluation in multi-model databases benchmarking |journal=Distributed and Parallel Databases |date=1 March 2021 |volume=39 |issue=1 |pages=1–33 |doi=10.1007/s10619-019-07279-6 |url=https://link.springer.com/article/10.1007/s10619-019-07279-6 |access-date=7 March 2025 |language=en |issn=1573-7578}}

Because AgensGraph is derived from PostgreSQL, its performance can be improved with PostgreSQL performance recommendation {{cite web |title=Chapter 14. Performance Tips |url=https://www.postgresql.org/docs/current/performance-tips.html |website=PostgreSQL Documentation |access-date=7 March 2025 |language=en |date=20 February 2025}} and using Graph Property Index.

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Because of Graph database popularity, An AgensGraph extension was proposed to The Apache Software Foundation.{{cite web |url= https://cwiki.apache.org/confluence/display/INCUBATOR/AGEProposal | title= AGEProposal - INCUBATOR - Apache Software Foundation | access-date=2025-02-18 | website=apache.org}} Proposal was accepted and moved to incubation in April 2020.

After two more years of development in June 2022 Apache® announced Apache AGE {{TM}} as Top Level Project as graph extension for PostgreSQL database.{{cite web |url= https://news.apache.org/foundation/entry/the-apache-software-foundation-announces83 | title= The Apache Software Foundation Announces Apache® AGE™ as a Top-Level Project | date= 8 June 2022 | access-date=2025-02-18}}{{cite web |url= https://age.apache.org/ | title= Apache AGE Graph Database - Apache AGE | access-date=2025-02-18| website=apache.org}}

{{Portal|Free and open-source software|Computer programming}}

• Graph Query Language (GQL)
• Cypher (query language)

{{Reflist|refs=

{{cite web |url= https://bitnine.tistory.com/263/ | title=Release Announcement AgensGraph 1.0.0|date= January 16, 2017 | access-date=2025-02-18}}

{{cite web |url= https://github.com/bitnine-oss/agensgraph/releases | title= Releases · bitnine-oss/agensgraph |website=github.com |date= January 26, 2022 | access-date=2025-02-18}}

{{cite web |url= https://github.com/bitnine-oss/agensgraph/ | title=AgensGraph, a transactional graph database based on PostgreSQL| website=GitHub| access-date=2025-03-07}}

{{cite book |last1=Ceri |first1=Stefano |last2=Bernasconi |first2=Anna |last3=Gagliardi |first3=Alessia |last4=Martinenghi |first4=Davide |last5=Bellomarini |first5=Luigi |last6=Magnanimi |first6=Davide |chapter=PG-Triggers: Triggers for Property Graphs |title=Companion of the 2024 International Conference on Management of Data |date=9 June 2024 |pages=373–385 |doi=10.1145/3626246.3653386|arxiv=2307.07354 |isbn=979-8-4007-0422-2 }}

{{cite web |title=Release AgensGraph v2.12.1 · bitnine-oss/agensgraph |url=https://github.com/bitnine-oss/agensgraph/releases/tag/v2.12.1 |website=GitHub |access-date=10 March 2025 |language=en}}

{{cite journal |last1=Guo |first1=Qingsong |last2=Zhang |first2=Chao |last3=Zhang |first3=Shuxun |last4=Lu |first4=Jiaheng |title=Multi-model query languages: taming the variety of big data |journal=Distributed and Parallel Databases |date=1 March 2024 |volume=42 |issue=1 |pages=31–71 |doi=10.1007/s10619-023-07433-1 |url=https://link.springer.com/article/10.1007/s10619-023-07433-1 |access-date=10 March 2025 |language=en |issn=1573-7578}}

{{cite web |title=Current Projects · openCypher |url=https://opencypher.org/projects/ |website=opencypher.org |access-date=17 March 2025}}

{{cite book |last1=Deutsch |first1=Alin |last2=Francis |first2=Nadime |last3=Green |first3=Alastair |last4=Hare |first4=Keith |last5=Li |first5=Bei |last6=Libkin |first6=Leonid |last7=Lindaaker |first7=Tobias |last8=Marsault |first8=Victor |last9=Martens |first9=Wim |last10=Michels |first10=Jan |last11=Murlak |first11=Filip |last12=Plantikow |first12=Stefan |last13=Selmer |first13=Petra |last14=van Rest |first14=Oskar |last15=Voigt |first15=Hannes |last16=Vrgoč |first16=Domagoj |last17=Wu |first17=Mingxi |last18=Zemke |first18=Fred |chapter=Graph Pattern Matching in GQL and SQL/PGQ |title=Proceedings of the 2022 International Conference on Management of Data |date=11 June 2022 |pages=2246–2258 |doi=10.1145/3514221.3526057|isbn=978-1-4503-9249-5 |url=https://www.pure.ed.ac.uk/ws/files/260606327/Graph_Pattern_Matching_DEUTSCH_DOA27012022_AFV.pdf }}

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• {{Official website|https://bitnine.net/}}
• {{GitHub|bitnine-oss/agensgraph}}

{{Draft categories|

:Category:Graph databases

:Category:Structured storage

:Category:Free database management systems

:Category:Free software programmed in C

:Category:NoSQL

}}

{{Drafts moved from mainspace|date=March 2025}}