DBMS > Apache Phoenix vs. Faircom DB vs. Greenplum vs. Microsoft SQL Server vs. SAP IQ

System Properties Comparison Apache Phoenix vs. Faircom DB vs. Greenplum vs. Microsoft SQL Server vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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.

Microsofts flagship relational DBMS

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

column-oriented

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	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

phoenix.apache.org

www.faircom.com/products/faircom-db

greenplum.org

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

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

phoenix.apache.org

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.greenplum.org

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

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

FairCom Corporation

Pivotal Software Inc.

Microsoft

SAP, formerly Sybase

Initial release

2014

1979

2005

1989

1994

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

V12, November 2020

7.0.0, September 2023

SQL Server 2022, November 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

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

Java

ANSI C, C++

C++

Server operating systems

Linux
Unix
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

schema free, schema optional, schema required, partial schema,

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

JDBC

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
ODBC

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C
Java
Perl
Python
R

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

yes

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

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

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

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication

yes, but depending on the SQL-Server Edition

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Fine grained access rights according to SQL-standard with additional protections for files

fine grained access rights according to SQL-standard

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