DBMS > Oracle vs. Pinecone vs. SAP IQ vs. Warp 10

System Properties Comparison Oracle vs. Pinecone vs. SAP IQ vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS

A managed, cloud-native vector database

Columnar RDBMS optimized for Big Data analytics

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

column-oriented

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	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

www.oracle.com/database

www.pinecone.io

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.warp10.io

Technical documentation

docs.oracle.com/en/database

docs.pinecone.io/docs/overview

help.sap.com/docs/SAP_IQ

www.warp10.io/content/02_Getting_started

Developer

Oracle

Pinecone Systems, Inc

SAP, formerly Sybase

SenX

Initial release

1980

2019

1994

2015

Current release

23c, September 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache License 2.0

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 and C++

Java

Server operating systems

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

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

Schemaless in JSON and XML columns

yes

schema-free

Typing

predefined data types such as float or date

yes

String, Number, 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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP API
Jupyter
WebSocket

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

Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

SAP/Sybase Replication Server

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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