DBMS > AnzoGraph DB vs. etcd vs. Faircom EDGE vs. Microsoft SQL Server vs. SpatiaLite

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

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

A distributed reliable key-value store

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

Spatial extension of SQLite

Primary database model

Graph DBMS
RDF store

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	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

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	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

cambridgesemantics.com/anzograph

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

www.faircom.com/products/faircom-edge

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

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

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

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

Cambridge Semantics

FairCom Corporation

Microsoft

Alessandro Furieri

Initial release

2018

1979

1989

2008

Current release

2.3, January 2021

3.4, August 2019

V3, October 2020

SQL Server 2022, November 2022

5.0.0, August 2020

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

commercial

Restricted, free version available

commercial

restricted free version is available

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

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Implementation language

ANSI C, C++

C++

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

Android
Linux

ARM, x86
Raspbian
Windows

Linux
Windows

server-less

Data scheme

Schema-free and OWL/RDFS-schema support

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

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

ANSI SQL queries

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

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)

Supported programming languages

C++
Java
Python

.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

Server-side scripts

Stored procedures

user defined functions and aggregates

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

Automatic sharding

File partitioning

Customizable business rules for partitioning

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

Access rights for users and roles

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

fine grained access rights according to SQL-standard

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