DBMS > Oracle vs. Qdrant vs. Sphinx vs. Teradata Aster vs. TigerGraph

System Properties Comparison Oracle vs. Qdrant vs. Sphinx vs. Teradata Aster vs. TigerGraph

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Widely used RDBMS

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

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

Platform for big data analytics on multistructured data sources and types

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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

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

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.oracle.com/database

github.com/qdrant/qdrant
qdrant.tech

sphinxsearch.com

www.tigergraph.com

Technical documentation

docs.oracle.com/en/database

qdrant.tech/documentation

sphinxsearch.com/docs

docs.tigergraph.com

Developer

Oracle

Qdrant

Sphinx Technologies Inc.

Teradata

Initial release

1980

2021

2001

2005

2017

Current release

23c, September 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

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++

Server operating systems

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

Docker
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

yes

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (SphinxQL)

yes

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
C#
C++
Java
Python
R

C++
Java

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

R packages

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Collection-level replication

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

SQL Map-Reduce Framework

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

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.

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

Key-based authentication

fine grained access rights according to SQL-standard

Role-based access control

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