DBMS > BigObject vs. Fujitsu Enterprise Postgres vs. OrigoDB vs. searchxml vs. SQLite

System Properties Comparison BigObject vs. Fujitsu Enterprise Postgres vs. OrigoDB vs. searchxml vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

A fully ACID in-memory object graph database

DBMS for structured and unstructured content wrapped with an application server

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store
Object oriented DBMS

Native XML DBMS
Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

bigobject.io

www.postgresql.fastware.com

origodb.com

www.searchxml.net/category/products

www.sqlite.org

Technical documentation

docs.bigobject.io

www.postgresql.fastware.com/product-manuals

origodb.com/docs

www.searchxml.net/support/handouts

www.sqlite.org/docs.html

Developer

BigObject, Inc.

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Robert Friberg et al

informationpartners gmbh

Dwayne Richard Hipp

Initial release

2015

2009

under the name LiveDB

2015

2000

Current release

Fujitsu Enterprise Postgres 14, January 2022

1.0

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

commercial

Open Source

Public Domain

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

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

.NET Client API
HTTP API
LINQ

RESTful HTTP API
WebDAV
XQuery
XSLT

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net

C++

most other programming languages supported via APIs

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

Server-side scripts

Stored procedures

Lua

user defined functions

yes

on the application server

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

partitioning by range, list and by hash

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

depending on model

yes

Transaction concepts

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

ACID

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

fine grained access rights according to SQL-standard

Role based authorization

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.