DBMS > Citus vs. Heroic vs. Oracle vs. Quasardb vs. Warp 10

System Properties Comparison Citus vs. Heroic vs. Oracle vs. Quasardb vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Widely used RDBMS

Distributed, high-performance timeseries database

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

Primary database model

Secondary database models

Document store

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	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.citusdata.com

github.com/spotify/heroic

www.oracle.com/database

quasar.ai

www.warp10.io

Technical documentation

docs.citusdata.com

spotify.github.io/heroic

docs.oracle.com/en/database

doc.quasar.ai/master

www.warp10.io/content/02_Getting_started

Developer

Spotify

Oracle

quasardb

SenX

Initial release

2010

2014

1980

2009

2015

Current release

8.1, December 2018

23c, September 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache License 2.0

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

Java

C and C++

C++

Java

Server operating systems

Linux

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

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

via Elasticsearch

yes

with tags

SQL

Support of SQL

yes

standard, with numerous extensions

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

PL/SQL

also stored procedures in Java possible

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

consistent hashing

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

by using LevelDB

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

Transient mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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