DBMS > IRONdb vs. MarkLogic vs. RethinkDB vs. Spark SQL vs. Transbase

System Properties Comparison IRONdb vs. MarkLogic vs. RethinkDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Operational and transactional Enterprise NoSQL database

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.circonus.com/solutions/time-series-database/

www.marklogic.com

rethinkdb.com

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

docs.circonus.com/irondb/category/getting-started

docs.marklogic.com

rethinkdb.com/docs

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

www.transaction.de/en/products/transbase/features.html

Developer

Circonus LLC.

MarkLogic Corp.

The Linux Foundation

since July 2017

Apache Software Foundation

Transaction Software GmbH

Initial release

2017

2001

2009

2014

1987

Current release

V0.10.20, January 2018

11.0, December 2022

2.4.1, August 2020

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

free development license

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

C and C++

C++

Scala

C and C++

Server operating systems

Linux

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

Schema can be enforced

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

string, binary, float, bool, date, geometry

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

SQL92

SQL-like DML and DDL statements

yes

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

yes

via XQuery or JavaScript

yes

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

range based

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

yes

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

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

Atomic single-document operations

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

User concepts

Access control

Role-based access control at the document and subdocument levels

yes

users and table-level permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

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