DBMS > Faircom DB vs. Prometheus vs. RethinkDB vs. SAP HANA vs. Ultipa

System Properties Comparison Faircom DB vs. Prometheus vs. RethinkDB vs. SAP HANA vs. Ultipa

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.

Open-source Time Series DBMS and monitoring system

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

In-memory, column based data store. Available as appliance or cloud service

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

www.faircom.com/products/faircom-db

prometheus.io

rethinkdb.com

www.sap.com/products/hana.html

www.ultipa.com

Technical documentation

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

prometheus.io/docs

rethinkdb.com/docs

help.sap.com/hana

www.ultipa.com/document

Developer

FairCom Corporation

The Linux Foundation

since July 2017

SAP

Ultipa

Initial release

1979

2015

2009

2010

2019

Current release

V12, November 2020

2.4.1, August 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based 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
Windows

Linux
OS X
Windows

Appliance or cloud-service

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

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
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

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

SQLScript, R

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

range based

yes

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).

yes

by Federation

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

none

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

User concepts

Access control

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

yes

users and table-level permissions

yes

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