DBMS > Apache Druid vs. EJDB vs. HugeGraph vs. mSQL

System Properties Comparison Apache Druid vs. EJDB vs. HugeGraph vs. mSQL

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A fast-speed and highly-scalable Graph DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Document store

Graph DBMS

Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Website

druid.apache.org

github.com/Softmotions/ejdb

github.com/hugegraph
hugegraph.apache.org

hughestech.com.au/products/msql

Technical documentation

druid.apache.org/docs/latest/design

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

hugegraph.apache.org/docs

Developer

Apache Software Foundation and contributors

Softmotions

Baidu

Hughes Technologies

Initial release

2012

2018

1994

Current release

29.0.1, April 2024

0.9

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GPLv2

Open Source

Apache Version 2.0

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Unix

server-less

Linux
macOS
Unix

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL for querying

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
RESTful HTTP/JSON API

in-process shared library

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Groovy
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

edges in graph

Transaction concepts

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users, roles and permissions

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