DBMS > Apache Druid vs. OpenQM vs. Oracle vs. Pinecone vs. TimescaleDB

System Properties Comparison Apache Druid vs. OpenQM vs. Oracle vs. Pinecone vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

QpenQM is a high-performance, self-tuning, multi-value DBMS

Widely used RDBMS

A managed, cloud-native vector database

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS
Time Series 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

Relational DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

druid.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.oracle.com/database

www.pinecone.io

www.timescale.com

Technical documentation

druid.apache.org/docs/latest/design

docs.oracle.com/en/database

docs.pinecone.io/docs/overview

docs.timescale.com

Developer

Apache Software Foundation and contributors

Rocket Software, originally Martin Phillips

Oracle

Pinecone Systems, Inc

Timescale

Initial release

2012

1993

1980

2019

2017

Current release

29.0.1, April 2024

3.4-12

23c, September 2023

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GPLv2, extended commercial license available

commercial

restricted free version is available

commercial

Open Source

Apache 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

Java

C and C++

Server operating systems

Linux
OS X
Unix

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

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

hosted

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

yes

with some exceptions

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL for querying

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Basic
C
Java
Objective C
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

Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

Sharding, horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

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

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'

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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