DBMS > BoltDB vs. Faircom EDGE vs. Microsoft SQL Server vs. MonetDB vs. SAP HANA

System Properties Comparison BoltDB vs. Faircom EDGE vs. Microsoft SQL Server vs. MonetDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

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

Primary database model

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
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	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

github.com/boltdb/bolt

www.faircom.com/products/faircom-edge

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

www.monetdb.org

www.sap.com/products/hana.html

Technical documentation

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

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

www.monetdb.org/Documentation

help.sap.com/hana

Developer

FairCom Corporation

Microsoft

MonetDB BV

SAP

Initial release

2013

1979

1989

2004

2010

Current release

V3, October 2020

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

MIT License

commercial

Restricted, free version available

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

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

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Implementation language

ANSI C, C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

SQL 2003 with some extensions

yes

APIs and other access methods

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

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

yes, in SQL, C, R

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

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

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

fine grained access rights according to SQL-standard

yes

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