DBMS > Bangdb vs. Heroic vs. JanusGraph vs. Oracle Rdb vs. Sequoiadb

System Properties Comparison Bangdb vs. Heroic vs. JanusGraph vs. Oracle Rdb vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A Graph DBMS optimized for distributed clusters

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

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Graph DBMS

Relational DBMS

Document store
Relational DBMS

Secondary database models

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	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

bangdb.com

github.com/spotify/heroic

janusgraph.org

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

www.sequoiadb.com

Technical documentation

docs.bangdb.com

spotify.github.io/heroic

docs.janusgraph.org

www.oracle.com/database/technologies/related/rdb-doc.html

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Sachin Sinha, BangDB

Spotify

Linux Foundation; originally developed as Titan by Aurelius

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sequoiadb Ltd.

Initial release

2012

2014

2017

1984

2013

Current release

BangDB 2.0, October 2021

0.6.3, February 2023

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

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++

Java

C++

Server operating systems

Linux

Linux
OS X
Unix
Windows

HP Open VMS

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

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

yes

oid, date, timestamp, binary, regex

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

via Elasticsearch

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

proprietary protocol using JSON

Supported programming languages

C
C#
C++
Java
Python

Clojure
Java
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

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

Sharding

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)

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes, on a single node

Document is locked during a transaction

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

User concepts

Access control

yes (enterprise version only)

User authentification and security via Rexster Graph Server

simple password-based access control

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