DBMS > Citus vs. Graph Engine vs. Microsoft Access vs. VoltDB

System Properties Comparison Citus vs. Graph Engine vs. Microsoft Access vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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.)

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store

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

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

www.citusdata.com

www.graphengine.io

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

www.voltdb.com

Technical documentation

docs.citusdata.com

www.graphengine.io/docs/manual

developer.microsoft.com/en-us/access

docs.voltdb.com

Developer

Microsoft

VoltDB Inc.

Initial release

2010

1992

2010

Current release

8.1, December 2018

1902 (16.0.11328.20222), March 2019

11.3, April 2022

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

MIT License

commercial

Bundled with Microsoft Office

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

.NET and C

C++

Java, C++

Server operating systems

Linux

.NET

Windows

Not a real database server, but making use of DLLs

Linux
OS X

for development

Data scheme

yes

Typing

predefined data types such as float or date

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

but not compliant to any SQL standard

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
F#
Visual Basic

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

since Access 2010 using the ACE-engine

Java

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

but no files for transaction logging

yes

Snapshots and command logging

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

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

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

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

Microsoft SQL Server regained rank 2 in the DB-Engines popularity ranking
3 December 2012, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

show all

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