DBMS > Apache Drill vs. HugeGraph vs. Postgres-XL

System Properties Comparison Apache Drill vs. HugeGraph vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

A fast-speed and highly-scalable Graph DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

drill.apache.org

github.com/hugegraph
hugegraph.apache.org

www.postgres-xl.org

Technical documentation

drill.apache.org/docs

hugegraph.apache.org/docs

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

Baidu

Initial release

2012

2018

2014

since 2012, originally named StormDB

Current release

1.20.3, January 2023

0.9

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Mozilla public license

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
Windows

Linux
macOS
Unix

Linux
macOS

Data scheme

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

XML type, but no XML query functionality

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C++

Groovy
Java
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Users, roles and permissions

fine grained access rights according to SQL-standard

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More resources

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