DBMS > EXASOL vs. Ingres vs. Oracle vs. Qdrant vs. SAP Adaptive Server

System Properties Comparison EXASOL vs. Ingres vs. Oracle vs. Qdrant vs. SAP Adaptive Server

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Well established RDBMS

Widely used RDBMS

A high-performance vector database with neural network or semantic-based matching

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Relational DBMS

Vector DBMS

Relational DBMS

Secondary database models

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

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

www.exasol.com

www.actian.com/databases/ingres

www.oracle.com/database

github.com/qdrant/qdrant
qdrant.tech

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

www.exasol.com/resources

docs.actian.com/ingres

docs.oracle.com/en/database

qdrant.tech/documentation

help.sap.com/docs/SAP_ASE

Developer

Exasol

Actian Corporation

Oracle

Qdrant

SAP, Sybase

Initial release

2000

1974

originally developed at University Berkely in early 1970s

1980

2021

1987

Current release

11.2, May 2022

23c, September 2023

16.0

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

commercial

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 and C++

Rust

C and C++

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

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

Docker
Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, 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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Java
Lua
Python
R

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

PL/SQL

also stored procedures in Java possible

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

Multi-source replication
Source-replica replication

Collection-level replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

Key-based authentication

fine grained access rights according to SQL-standard

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