DBMS > AllegroGraph vs. Apache Drill vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. Vertica

System Properties Comparison AllegroGraph vs. Apache Drill vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. Vertica

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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.)

Globally distributed, horizontally scalable, multi-model database service

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store
Relational DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

allegrograph.com

drill.apache.org

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

azure.microsoft.com/services/cosmos-db

www.vertica.com

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

drill.apache.org/docs

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

vertica.com/documentation

Developer

Franz Inc.

Apache Software Foundation

Microsoft

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2004

2012

1992

2014

2005

Current release

8.0, December 2023

1.20.3, January 2023

1902 (16.0.11328.20222), March 2019

12.0.3, January 2023

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2

commercial

Bundled with Microsoft Office

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

hosted

Linux

Data scheme

yes

RDF schemas

schema-free

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

JSON 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.

bulk load of XML files possible

Secondary indexes

yes

All properties auto-indexed by default

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SPARQL is used as query language

SQL SELECT statement is SQL:2003 compliant

yes

but not compliant to any SQL standard

SQL-like query language

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C++

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

yes

since Access 2010 using the ACE-engine

JavaScript

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

since Access 2010 using the ACE-engine

JavaScript

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

none

Sharding

Implicit feature of the cloud service

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

Implicit feature of the cloud service

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Depending on the underlying data source

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.

Depending on the underlying data source

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Depending on the underlying data source

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Key customers

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Licensing and pricing models

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