DBMS > Greenplum vs. IRONdb vs. LevelDB vs. Microsoft SQL Server vs. RDF4J

System Properties Comparison Greenplum vs. IRONdb vs. LevelDB vs. Microsoft SQL Server vs. RDF4J

Editorial information provided by DB-Engines

Name

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

Description

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Microsofts flagship relational DBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

greenplum.org

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

github.com/google/leveldb

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

rdf4j.org

Technical documentation

docs.greenplum.org

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

github.com/google/leveldb/blob/main/doc/index.md

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

rdf4j.org/documentation

Developer

Pivotal Software Inc.

Circonus LLC.

Google

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2005

2017

2011

1989

2004

Current release

7.0.0, September 2023

V0.10.20, January 2018

1.23, February 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Java

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

yes

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

yes

APIs and other access methods

JDBC
ODBC

HTTP API

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
Java
Perl
Python
R

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes

yes, in Lua

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

none

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

configurable replication factor, datacenter aware

none

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

in-memory storage is supported as well

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

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