DBMS > Amazon DocumentDB vs. Datomic vs. Dgraph vs. JaguarDB vs. Microsoft SQL Server

System Properties Comparison Amazon DocumentDB vs. Datomic vs. Dgraph vs. JaguarDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Distributed and scalable native Graph DBMS

Performant, highly scalable DBMS for AI and IoT applications

Microsofts flagship relational DBMS

Primary database model

Document store

Relational DBMS

Graph DBMS

Key-value store
Vector 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	1.91
Rank	#131	Overall
	#24	Document stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

aws.amazon.com/documentdb

www.datomic.com

dgraph.io

www.jaguardb.com

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

Technical documentation

aws.amazon.com/documentdb/resources

docs.datomic.com

dgraph.io/docs

www.jaguardb.com/support.html

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

Developer

Cognitect

Dgraph Labs, Inc.

DataJaguar, Inc.

Microsoft

Initial release

2019

2012

2016

2015

1989

Current release

1.0.6735, June 2023

3.3 July 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

Open Source

GPL V3.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, Clojure

C++

the server part. Clients available in other languages

C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

Linux

Linux
Windows

Data scheme

schema-free

yes

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

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

JDBC
ODBC

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

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
Java

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

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

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

Server-side scripts

Stored procedures

yes

Transaction Functions

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

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

But extensive use of caching in the application peers

Synchronous replication via Raft

Multi-source replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users and roles

Planned for future releases

rights management via user accounts

fine grained access rights according to SQL-standard

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