DBMS > Blueflood vs. GBase vs. Oracle Berkeley DB vs. OrigoDB vs. Postgres-XL

System Properties Comparison Blueflood vs. GBase vs. Oracle Berkeley DB vs. OrigoDB vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Widely used in-process key-value store

A fully ACID in-memory object graph database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

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

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

blueflood.io

www.gbase.cn

www.oracle.com/database/technologies/related/berkeleydb.html

origodb.com

www.postgres-xl.org

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.oracle.com/cd/E17076_05/html/index.html

origodb.com/docs

www.postgres-xl.org/documentation

Developer

Rackspace

General Data Technology Co., Ltd.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Robert Friberg et al

Initial release

2013

2004

1994

2009

under the name LiveDB

2014

since 2012, originally named StormDB

Current release

GBase 8a, GBase 8s, GBase 8c

18.1.40, May 2020

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

commercial license available

Open Source

Mozilla public license

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

Java

C, Java, Python

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
OS X

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
Windows

Linux
macOS

Data scheme

predefined scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

yes

only with the Berkeley DB XML edition

can be achieved using .NET

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

SQL interfaced based on SQLite is available

yes

distributed, parallel query execution

APIs and other access methods

HTTP REST

ADO.NET
C API
JDBC
ODBC

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

yes

only for the SQL API

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning (by range, list and hash) and vertical partitioning

none

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

yes

Role based authorization

fine grained access rights according to SQL-standard

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