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

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

Editorial information provided by DB-Engines

Name

Description

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

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

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

Primary database model

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	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

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.exasol.com

www.oracle.com/database

github.com/qdrant/qdrant
qdrant.tech

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

sphinxsearch.com

Technical documentation

www.exasol.com/resources

docs.oracle.com/en/database

qdrant.tech/documentation

help.sap.com/docs/SAP_ASE

sphinxsearch.com/docs

Developer

Exasol

Oracle

Qdrant

SAP, Sybase

Sphinx Technologies Inc.

Initial release

2000

1980

2021

1987

2001

Current release

23c, September 2023

16.0

3.5.1, February 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2, commercial licence available

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++

C++

Server operating systems

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

Docker
Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
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.

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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)

Proprietary protocol

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

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

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Collection-level replication

Multi-source replication
Source-replica replication

none

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

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

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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