DBMS > Amazon DocumentDB vs. EsgynDB vs. JSqlDb vs. RDF4J vs. XTDB

System Properties Comparison Amazon DocumentDB vs. EsgynDB vs. JSqlDb vs. RDF4J vs. XTDB

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

JavaScript Query Language Database, stores JavaScript objects and primitives

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store

Relational DBMS

Document store
Object oriented DBMS

RDF store

Document store

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

aws.amazon.com/documentdb

www.esgyn.cn

jsqldb.org (offline)

rdf4j.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

aws.amazon.com/documentdb/resources

rdf4j.org/documentation

www.xtdb.com/docs

Developer

Esgyn

Konrad von Backstrom

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Juxt Ltd.

Initial release

2019

2015

2018

2004

2019

Current release

0.8, December 2018

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

MIT License

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++, Java

Java

Clojure

Server operating systems

hosted

Linux

Linux
macOS
Windows

Linux
OS X
Unix
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST
JDBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC/ADO.Net

JavaScript

Java
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication between multi datacenters

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

in-memory storage is supported as well

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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