DBMS > Bangdb vs. Dgraph vs. DolphinDB vs. JanusGraph vs. Netezza

System Properties Comparison Bangdb vs. Dgraph vs. DolphinDB vs. JanusGraph vs. Netezza

Editorial information provided by DB-Engines

Name

Description

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

Distributed and scalable native Graph DBMS

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

www.ibm.com/products/netezza

Technical documentation

docs.bangdb.com

dgraph.io/docs

docs.dolphindb.cn/en/help200/index.html

docs.janusgraph.org

Developer

Sachin Sinha, BangDB

Dgraph Labs, Inc.

DolphinDB, Inc

Linux Foundation; originally developed as Titan by Aurelius

IBM

Initial release

2012

2016

2018

2017

2000

Current release

BangDB 2.0, October 2021

v2.00.4, January 2022

0.6.3, February 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

commercial

free community version available

Open Source

Apache 2.0

commercial

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++

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Linux

included in appliance

Data scheme

schema-free

yes

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Java
Python

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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Clojure
Java
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

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

yes

horizontal partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Synchronous replication via Raft

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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)

Planned for future releases

Administrators, Users, Groups

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

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