DBMS > Kyligence Enterprise vs. MarkLogic vs. Microsoft Azure Table Storage vs. Oracle vs. Warp 10

System Properties Comparison Kyligence Enterprise vs. MarkLogic vs. Microsoft Azure Table Storage vs. Oracle vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, built on top of Apache Kylin

Operational and transactional Enterprise NoSQL database

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used RDBMS

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

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Wide column store

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

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

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

kyligence.io/kyligence-enterprise

www.progress.com/marklogic

azure.microsoft.com/en-us/services/storage/tables

www.oracle.com/database

www.warp10.io

Technical documentation

www.progress.com/marklogic/documentation

docs.oracle.com/en/database

www.warp10.io/content/02_Getting_started

Developer

Kyligence, Inc.

MarkLogic Corp.

Microsoft

Oracle

SenX

Initial release

2016

2001

2012

1980

2015

Current release

11.0, December 2022

23c, September 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C and C++

Java

Server operating systems

Linux

Linux
OS X
Windows

hosted

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

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

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

ANSI SQL for queries (using Apache Calcite)

yes

SQL92

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API
Jupyter
WebSocket

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

PL/SQL

also stored procedures in Java possible

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

can be realized in PL/SQL

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

can act as a resource manager in an XA/JTA transaction

optimistic locking

ACID

isolation level can be parameterized

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, with Range Indexes

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Role-based access control at the document and subdocument levels

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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