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

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

Editorial information provided by DB-Engines

Name

Description

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.

DBMS for storing time series, events and metrics

Microsofts flagship relational DBMS

Columnar RDBMS optimized for Big Data analytics

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

column-oriented

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with GEO package

Document store
Graph DBMS
Spatial DBMS

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

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	9.23
Rank	#47	Overall
	#30	Relational DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Website

www.faircom.com/products/faircom-db

greenplum.org

www.influxdata.com/products/influxdb-overview

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

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

Technical documentation

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

docs.greenplum.org

docs.influxdata.com/influxdb

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

help.sap.com/docs/SAP_IQ

Developer

FairCom Corporation

Pivotal Software Inc.

Microsoft

SAP, formerly Sybase

Initial release

1979

2005

2013

1989

1994

Current release

V12, November 2020

7.0.0, September 2023

2.7.5, January 2024

SQL Server 2022, November 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

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

ANSI C, C++

C++

Server operating systems

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

easily portable to other OSs

Linux

Linux
OS X

through Homebrew

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

Numeric data and Strings

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, ANSI SQL with proprietary extensions

yes

SQL-like query language

yes

APIs and other access methods

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

JDBC
ODBC

HTTP API
JSON over UDP

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

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

C
Java
Perl
Python
R

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

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

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

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

in enterprise version only

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

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

selectable replication factor

in enterprise version only

yes, but depending on the SQL-Server Edition

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Depending on used storage engine

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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