DBMS > Amazon Redshift vs. OpenEdge vs. Oracle Berkeley DB vs. Oracle Rdb vs. Sphinx

System Properties Comparison Amazon Redshift vs. OpenEdge vs. Oracle Berkeley DB vs. Oracle Rdb vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Application development environment with integrated database management system

Widely used in-process key-value store

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Search engine

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	3.75
Rank	#88	Overall
	#47	Relational DBMS

Score	2.52
Rank	#114	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

aws.amazon.com/redshift

www.progress.com/openedge

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

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

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/redshift

documentation.progress.com/output/ua/OpenEdge_latest

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

www.oracle.com/database/technologies/related/rdb-doc.html

sphinxsearch.com/docs

Developer

Amazon (based on PostgreSQL)

Progress Software Corporation

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sphinx Technologies Inc.

Initial release

2012

1984

1994

1984

2001

Current release

OpenEdge 12.2, March 2020

18.1.40, May 2020

7.4.1.1, 2021

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

commercial license available

commercial

Open Source

GPL version 2, commercial licence available

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

C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

HP Open VMS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

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

Secondary indexes

restricted

yes

full-text index on all search fields

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

close to SQL 92

yes

SQL interfaced based on SQLite is available

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

Progress proprietary ABL (Advanced Business Language)

.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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

since Version 11.4

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

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

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

Users and groups

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