DBMS > AgensGraph vs. Faircom EDGE vs. Lovefield vs. Microsoft Access vs. Microsoft Azure Synapse Analytics

System Properties Comparison AgensGraph vs. Faircom EDGE vs. Lovefield vs. Microsoft Access vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Embeddable relational database for web apps written in pure JavaScript

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Graph DBMS
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Website

bitnine.net/agensgraph

www.faircom.com/products/faircom-edge

google.github.io/lovefield

www.microsoft.com/en-us/microsoft-365/access

azure.microsoft.com/services/synapse-analytics

Technical documentation

bitnine.net/documentation

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

github.com/google/lovefield/blob/master/docs/spec_index.md

developer.microsoft.com/en-us/access

docs.microsoft.com/azure/synapse-analytics

Developer

Bitnine Global Inc.

FairCom Corporation

Google

Microsoft

Initial release

2016

1979

2014

1992

2016

Current release

2.1, December 2018

V3, October 2020

2.1.12, February 2017

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

ANSI C, C++

JavaScript

C++

Server operating systems

Linux
OS X
Windows

Android
Linux

ARM, x86
Raspbian
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

depending on used data model

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

yes

Typing

predefined data types such as float or date

yes

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

SQL-like query language

via JavaScript builder pattern

yes

but not compliant to any SQL standard

yes

APIs and other access methods

Cypher Query Language
JDBC

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

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

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

JavaScript

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C#
Java
PHP

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

since Access 2010 using the ACE-engine

Transact SQL

Triggers

yes

Using read-only observers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

File partitioning

Customizable business rules for partitioning

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

but no files for transaction logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

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

a simple user-level security was built in till version Access 2003

yes

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

MS Access drops in DB-Engines Ranking
2 May 2013, Paul Andlinger

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3 December 2012, Matthias Gelbmann

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3 October 2012, Matthias Gelbmann, Paul Andlinger

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