DBMS > Bangdb vs. Ehcache vs. Heroic vs. JanusGraph

System Properties Comparison Bangdb vs. Ehcache vs. Heroic vs. JanusGraph

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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

A widely adopted Java cache with tiered storage options

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Website

bangdb.com

www.ehcache.org

github.com/spotify/heroic

janusgraph.org

Technical documentation

docs.bangdb.com

www.ehcache.org/documentation

spotify.github.io/heroic

docs.janusgraph.org

Developer

Sachin Sinha, BangDB

Terracotta Inc, owned by Software AG

Spotify

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2012

2009

2014

2017

Current release

BangDB 2.0, October 2021

3.10.0, March 2022

0.6.3, February 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

Apache 2.0

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

Server operating systems

Linux

All OS with a Java VM

Linux
OS X
Unix
Windows

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

via Elasticsearch

yes

SQL

Support of SQL

SQL like support with command line tool

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JCache

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C#
C++
Java
Python

Java

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Cache Event Listeners

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

by using Terracotta Server

Sharding

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

by using Terracotta Server

yes

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

Tunable Consistency (Strong, Eventual, Weak)

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

supports JTA and can work as an XA resource

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 a tiered cache-storage approach

yes

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

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)

User authentification and security via Rexster Graph Server

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