DBMS > Citus vs. IRONdb vs. Microsoft SQL Server vs. Postgres-XL vs. Sequoiadb

System Properties Comparison Citus vs. IRONdb vs. Microsoft SQL Server vs. Postgres-XL vs. Sequoiadb

Editorial information provided by DB-Engines

Name

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

Description

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

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

Microsofts flagship relational DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.citusdata.com

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

www.microsoft.com/en-us/sql-server

www.postgres-xl.org

www.sequoiadb.com

Technical documentation

docs.citusdata.com

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

learn.microsoft.com/en-US/sql/sql-server

www.postgres-xl.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Circonus LLC.

Microsoft

Sequoiadb Ltd.

Initial release

2010

2017

1989

2014

since 2012, originally named StormDB

2013

Current release

8.1, December 2018

V0.10.20, January 2018

SQL Server 2022, November 2022

10 R1, October 2018

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

restricted free version is available

Open Source

Mozilla public license

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C and C++

C++

Server operating systems

Linux

Linux
Windows

Linux
macOS

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

oid, date, timestamp, binary, regex

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

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

yes

distributed, parallel query execution

SQL-like query language

APIs and other access methods

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

HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

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

proprietary protocol using JSON

Supported programming languages

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

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

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

yes, in Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

configurable replication factor, datacenter aware

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

MVCC

Document is locked during a transaction

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

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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