DBMS > AllegroGraph vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. Kyligence Enterprise

System Properties Comparison AllegroGraph vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. Kyligence Enterprise

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A distributed analytics engine for big data, built on top of Apache Kylin

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Document store

Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.84
Rank	#204	Overall
	#35	Document stores
	#18	Graph DBMS
	#7	RDF stores
	#10	Vector DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.44
Rank	#259	Overall
	#118	Relational DBMS

Website

allegrograph.com

www.esgyn.cn

firebase.google.com/products/realtime-database

cloud.google.com/bigtable

kyligence.io/kyligence-enterprise

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

firebase.google.com/docs/database

cloud.google.com/bigtable/docs

Developer

Franz Inc.

Esgyn

Google

acquired by Google 2014

Google

Kyligence, Inc.

Initial release

2004

2015

2012

2015

2016

Current release

8.0, December 2023

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

Java

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux

Data scheme

yes

RDF schemas

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

bulk load of XML files possible

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

RESTful HTTP API
SPARQL

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Java Stored Procedures

limited functionality with using 'rules'

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

Internal replication in Colossus, and regional replication between two clusters in different zones

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

More information provided by the system vendor

News

AllegroGraph Named a 2024 Trend Setting Product
16 September 2024

Gartner recognized Franz Inc. as a Key Neuro-Symbolic AI Provider in 2024 Hype Cycle for AI
10 September 2024

Next-Generation Cybersecurity: Integrating Knowledge Graphs and Neuro-Symbolic AI with STIX and TAXII
10 September 2024

Pruning Cycles in UMLS Metathesaurus: A Neuro Symbolic AI Approach
9 September 2024

Podcast – Gartner AI Hype Cycle – Knowledge Graphs and Neuro-Symbolic AI
24 August 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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