DBMS > AgensGraph vs. Lovefield vs. openGemini vs. Quasardb

System Properties Comparison AgensGraph vs. Lovefield vs. openGemini vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Embeddable relational database for web apps written in pure JavaScript

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Distributed, high-performance timeseries database

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

bitnine.net/agensgraph

google.github.io/lovefield

www.opengemini.org
github.com/openGemini

quasar.ai

Technical documentation

bitnine.net/documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.opengemini.org/guide

doc.quasar.ai/master

Developer

Bitnine Global Inc.

Google

Huawei and openGemini community

quasardb

Initial release

2016

2014

2022

2009

Current release

2.1, December 2018

2.1.12, February 2017

1.1, July 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

Server operating systems

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

yes

integer and binary

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

HTTP REST

HTTP API

Supported programming languages

C
Java
JavaScript
Python

JavaScript

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by using LevelDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators and common users accounts

Cryptographically strong user authentication and audit trail

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