DBMS > HugeGraph vs. LeanXcale vs. MarkLogic vs. Sadas Engine vs. ToroDB

System Properties Comparison HugeGraph vs. LeanXcale vs. MarkLogic vs. Sadas Engine vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A fast-speed and highly-scalable Graph DBMS

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Operational and transactional Enterprise NoSQL database

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Graph DBMS

Key-value store
Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Document store

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.leanxcale.com

www.marklogic.com

www.sadasengine.com

github.com/torodb/server

Technical documentation

hugegraph.apache.org/docs

docs.marklogic.com

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

Developer

Baidu

LeanXcale

MarkLogic Corp.

SADAS s.r.l.

8Kdata

Initial release

2018

2015

2001

2006

2016

Current release

0.9

11.0, December 2022

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

free trial version available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java

Server operating systems

Linux
macOS
Unix

Linux
OS X
Windows

AIX
Linux
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Schema can be enforced

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

through Apache Derby

yes

SQL92

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

JDBC
ODBC
Proprietary protocol

Supported programming languages

Groovy
Java
Python

C
Java
Scala

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

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

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

Concurrency

Support for concurrent manipulation of data

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

yes, with Range Indexes

yes

managed by 'Learn by Usage'

User concepts

Access control

Users, roles and permissions

Role-based access control at the document and subdocument levels

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

Access rights for users and roles

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