DBMS > EJDB vs. Galaxybase vs. Google BigQuery vs. H2

System Properties Comparison EJDB vs. Galaxybase vs. Google BigQuery vs. H2

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Scalable, ACID-compliant native distributed parallel graph platform

Large scale data warehouse service with append-only tables

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Document store

Graph DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Website

github.com/Softmotions/ejdb

galaxybase.com

cloud.google.com/bigquery

www.h2database.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/bigquery/docs

www.h2database.com/html/main.html

Developer

Softmotions

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

Thomas Mueller

Initial release

2012

2017

2010

2005

Current release

Nov 20, November 2021

2.2.220, July 2023

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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 and Java

Java

Server operating systems

server-less

Linux

hosted

All OS with a Java VM

Data scheme

schema-free

Strong typed schema

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Go
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

user defined procedures and functions

user defined functions

in JavaScript

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

yes, multi-version concurrency control (MVCC)

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

Role-based access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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