DBMS > etcd vs. Faircom EDGE vs. Microsoft SQL Server vs. SpaceTime vs. SpatiaLite

System Properties Comparison etcd vs. Faircom EDGE vs. Microsoft SQL Server vs. SpaceTime vs. SpatiaLite

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Spatial extension of SQLite

Primary database model

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	7.25
Rank	#54	Overall
	#5	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	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.faircom.com/products/faircom-edge

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

www.mireo.com/spacetime

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

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

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

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

FairCom Corporation

Microsoft

Mireo

Alessandro Furieri

Initial release

1979

1989

2020

2008

Current release

3.4, August 2019

V3, October 2020

SQL Server 2022, November 2022

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Restricted, free version available

commercial

restricted free version is available

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

FreeBSD
Linux
Windows

experimental

Android
Linux

ARM, x86
Raspbian
Windows

Linux
Windows

Linux

server-less

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

A subset of ANSI SQL is implemented

yes

APIs and other access methods

gRPC
JSON over HTTP

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)

RESTful HTTP API

Supported programming languages

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

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++
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

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

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

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

Fixed-grid hypercubes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes, but depending on the SQL-Server Edition

Real-time block device replication (DRBD)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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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