DBMS > AgensGraph vs. Firebase Realtime Database vs. GridDB vs. SQLite vs. Ultipa

System Properties Comparison AgensGraph vs. Firebase Realtime Database vs. GridDB vs. SQLite vs. Ultipa

Editorial information provided by DB-Engines

Name

Description

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

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

Scalable in-memory time series database optimized for IoT and Big Data

Widely used embeddable, in-process RDBMS

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#338	Overall
	#32	Graph DBMS

Website

bitnine.net/agensgraph

firebase.google.com/products/realtime-database

griddb.net

www.sqlite.org

www.ultipa.com

Technical documentation

bitnine.net/documentation

firebase.google.com/docs/database

docs.griddb.net

www.sqlite.org/docs.html

www.ultipa.com/document

Developer

Bitnine Global Inc.

Google

acquired by Google 2014

Toshiba Corporation

Dwayne Richard Hipp

Ultipa

Initial release

2016

2012

2013

2000

2019

Current release

2.1, December 2018

5.1, August 2022

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Public Domain

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++

Server operating systems

Linux
OS X
Windows

hosted

Linux

server-less

Data scheme

depending on used data model

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

yes

SQL-92 is not fully supported

APIs and other access methods

Cypher Query Language
JDBC

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

Java
JavaScript
Objective-C

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

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

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Access rights for users can be defined per database

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