DBMS > EJDB vs. Google Cloud Bigtable vs. OrigoDB vs. Tibero

System Properties Comparison EJDB vs. Google Cloud Bigtable vs. OrigoDB vs. Tibero

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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)

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 fully ACID in-memory object graph database

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Document store

Key-value store
Wide column store

Document store
Object oriented DBMS

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

github.com/Softmotions/ejdb

cloud.google.com/bigtable

origodb.com

us.tmaxsoft.com/products/tibero

Technical documentation

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

cloud.google.com/bigtable/docs

origodb.com/docs

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Softmotions

Google

Robert Friberg et al

TmaxSoft

Initial release

2012

2015

2009

under the name LiveDB

2003

Current release

6, April 2015

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

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 and Assembler

Server operating systems

server-less

hosted

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

User defined using .NET types and collections

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.

can be achieved using .NET

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

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

.NET Client API
HTTP API
LINQ

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

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

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

.Net

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

Persistent Stored Procedure (PSM)

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

depending on model

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

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

Role based authorization

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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