DBMS > EJDB vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage vs. RDFox

System Properties Comparison EJDB vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A Wide Column Store for rapid development using massive semi-structured datasets

High performance knowledge graph and semantic reasoning engine

Primary database model

Secondary database models

Relational DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Website

github.com/Softmotions/ejdb

azure.microsoft.com/services/synapse-analytics

azure.microsoft.com/en-us/services/storage/tables

www.oxfordsemantic.tech

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.microsoft.com/azure/synapse-analytics

docs.oxfordsemantic.tech

Developer

Softmotions

Microsoft

Oxford Semantic Technologies

Initial release

2012

2016

2012

2017

Current release

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

GPLv2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

server-less

hosted

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF schemas

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

ADO.NET
JDBC
ODBC

RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
Java
PHP

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

C
Java

Server-side scripts

Stored procedures

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

yes

Access rights based on private key authentication or shared access signatures

Roles, resources, and access types

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