DBMS > Dgraph vs. LevelDB vs. MarkLogic vs. Microsoft SQL Server vs. Sadas Engine

System Properties Comparison Dgraph vs. LevelDB vs. MarkLogic vs. Microsoft SQL Server vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Operational and transactional Enterprise NoSQL database

Microsofts flagship relational DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Graph DBMS

Key-value store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

dgraph.io

github.com/google/leveldb

www.marklogic.com

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

www.sadasengine.com

Technical documentation

dgraph.io/docs

github.com/google/leveldb/blob/main/doc/index.md

docs.marklogic.com

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Dgraph Labs, Inc.

Google

MarkLogic Corp.

Microsoft

SADAS s.r.l.

Initial release

2016

2011

2001

1989

2006

Current release

1.23, February 2021

11.0, December 2022

SQL Server 2022, November 2022

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

commercial

restricted free version is available

commercial

restricted free version is available

commercial

free trial version available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

Linux
OS X
Windows

Linux
Windows

AIX
Linux
Windows

Data scheme

schema-free

Schema can be enforced

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

yes

SQL92

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

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

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

none

yes

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

yes, with Range Indexes

yes

managed by 'Learn by Usage'

User concepts

Access control

Planned for future releases

Role-based access control at the document and subdocument levels

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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