DBMS > BaseX vs. Drizzle vs. HBase vs. NebulaGraph vs. Postgres-XL

System Properties Comparison BaseX vs. Drizzle vs. HBase vs. NebulaGraph vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Wide-column store based on Apache Hadoop and on concepts of BigTable

A distributed, linear scalable, high perfomant Graph DBMS

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.90
Rank	#136	Overall
	#4	Native XML DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	2.12
Rank	#125	Overall
	#10	Graph DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

basex.org

hbase.apache.org

github.com/vesoft-inc/nebula
www.nebula-graph.io

www.postgres-xl.org

Technical documentation

docs.basex.org

hbase.apache.org/book.html

docs.nebula-graph.io

www.postgres-xl.org/documentation

Developer

BaseX GmbH

Drizzle project, originally started by Brian Aker

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Vesoft Inc.

Initial release

2007

2008

2019

2014

since 2012, originally named StormDB

Current release

10.7, August 2023

7.2.4, September 2012

2.3.4, January 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

BSD license

Open Source

GNU GPL

Open Source

Apache version 2

Open Source

Apache Version 2.0 + Common Clause 1.0

Open Source

Mozilla public license

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

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
Unix
Windows

using Cygwin

Linux

Linux
macOS

Data scheme

schema-free

yes

schema-free, schema definition possible

Strong typed schema

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

options to bring your own types, AVRO

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

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC

Java API
RESTful HTTP API
Thrift

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

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

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C
C++
Java
PHP

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C++
Go
Java
PHP
Python

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

Server-side scripts

Stored procedures

yes

Coprocessors in Java

user defined functions

Triggers

yes

via events

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Causal Clustering using Raft protocol

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

multiple readers, single writer

ACID

Single row ACID (across millions of columns)

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Users with fine-grained authorization concept on 4 levels

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
» more

Competitive advantages

NebulaGraph boasts the world's only graph database solution that is able to host...
» more

Typical application scenarios

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
» more

Key customers

Companies from a variety of industries have implemented NebulaGraph Database in production,...
» more

Market metrics

At our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
» more

Licensing and pricing models

NebulaGraph is open source and free to use under Apache 2.0 license.
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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