DBMS > Apache Drill vs. JanusGraph vs. Microsoft Access vs. Microsoft SQL Server

System Properties Comparison Apache Drill vs. JanusGraph vs. Microsoft Access vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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.)

Microsofts flagship relational DBMS

Primary database model

Document store
Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

drill.apache.org

janusgraph.org

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

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

Technical documentation

drill.apache.org/docs

docs.janusgraph.org

developer.microsoft.com/en-us/access

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

Developer

Apache Software Foundation

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Initial release

2012

2017

1992

1989

Current release

1.20.3, January 2023

0.6.3, February 2023

1902 (16.0.11328.20222), March 2019

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Windows

Not a real database server, but making use of DLLs

Linux
Windows

Data scheme

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

but not compliant to any SQL standard

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C++

Clojure
Java
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

yes

since Access 2010 using the ACE-engine

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

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

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

Durability

Support for making data persistent

Depending on the underlying data source

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

yes

User concepts

Access control

Depending on the underlying data source

User authentification and security via Rexster Graph Server

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

fine grained access rights according to SQL-standard

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