DBMS > Bangdb vs. Greenplum vs. NebulaGraph vs. Oracle Berkeley DB

System Properties Comparison Bangdb vs. Greenplum vs. NebulaGraph vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

A distributed, linear scalable, high perfomant Graph DBMS

Widely used in-process key-value store

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Graph DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	2.23
Rank	#116	Overall
	#10	Graph DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

bangdb.com

greenplum.org

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

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

docs.bangdb.com

docs.greenplum.org

docs.nebula-graph.io

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Sachin Sinha, BangDB

Pivotal Software Inc.

Vesoft Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2012

2005

2019

1994

Current release

BangDB 2.0, October 2021

7.0.0, September 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Apache Version 2.0 + Common Clause 1.0

Open Source

commercial license available

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

C, C++

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

Strong typed schema

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

since Version 4.2

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

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

SQL like support with command line tool

yes

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC

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

Supported programming languages

C
C#
C++
Java
Python

C
Java
Perl
Python
R

.Net
C++
Go
Java
PHP
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes, Notifications (with Streaming only)

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

Causal Clustering using Raft protocol

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

using RocksDB

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Role-based access control

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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