DBMS > MarkLogic vs. Oracle vs. Rockset vs. Spark SQL vs. Teradata Aster

System Properties Comparison MarkLogic vs. Oracle vs. Rockset vs. Spark SQL vs. Teradata Aster

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

Operational and transactional Enterprise NoSQL database

Widely used RDBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Spark SQL is a component on top of 'Spark Core' for structured data processing

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Document store

Relational 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
Search engine

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

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

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.marklogic.com

www.oracle.com/database

rockset.com

spark.apache.org/sql

Technical documentation

docs.marklogic.com

docs.oracle.com/en/database

docs.rockset.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

MarkLogic Corp.

Oracle

Rockset

Apache Software Foundation

Teradata

Initial release

2001

1980

2019

2014

2005

Current release

11.0, December 2022

23c, September 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

commercial

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++

C and C++

C++

Scala

Server operating systems

Linux
OS X
Windows

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

hosted

Linux
OS X
Windows

Linux

Data scheme

schema-free

Schema can be enforced

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

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

yes

in Aster File Store

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL92

yes

with proprietary extensions

Read-only SQL queries, including JOINs

SQL-like DML and DDL statements

yes

APIs and other access methods

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
Perl
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

Go
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

PL/SQL

also stored procedures in Java possible

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Automatic sharding

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

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

yes

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

can be realized in PL/SQL

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

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, with Range Indexes

yes

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

User concepts

Access control

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

fine grained access rights according to SQL-standard

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