DBMS > Amazon Redshift vs. Citus vs. Manticore Search vs. Oracle vs. SAP SQL Anywhere

System Properties Comparison Amazon Redshift vs. Citus vs. Manticore Search vs. Oracle vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Multi-storage database for search, including full-text search.

Widely used RDBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

aws.amazon.com/redshift

www.citusdata.com

manticoresearch.com

www.oracle.com/database

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.aws.amazon.com/redshift

docs.citusdata.com

manual.manticoresearch.com

docs.oracle.com/en/database

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Amazon (based on PostgreSQL)

Manticore Software

Oracle

SAP

formerly Sybase

Initial release

2012

2010

2017

1980

1992

Current release

8.1, December 2018

6.0, February 2023

23c, September 2023

17, July 2015

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

GPL version 2

commercial

restricted free version is available

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++

C and C++

Server operating systems

hosted

Linux

FreeBSD
Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

Fixed schema

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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

specific XML type available, but no XML query functionality

Can index from XML

yes

Secondary indexes

restricted

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

standard, with numerous extensions

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined functions

PL/SQL

also stored procedures in Java possible

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

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

isolated transactions for atomic changes and binary logging for safe writes

ACID

isolation level can be parameterized

ACID

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 Manticore index.

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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