DBMS > Bangdb vs. InterSystems Caché vs. JanusGraph vs. Riak KV

System Properties Comparison Bangdb vs. InterSystems Caché vs. JanusGraph vs. Riak KV

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

A multi-model DBMS and application server

A Graph DBMS optimized for distributed clusters

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

Distributed, fault tolerant key-value store

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Graph DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Spatial DBMS

Document store

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	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

bangdb.com

www.intersystems.com/products/cache

janusgraph.org

Technical documentation

docs.bangdb.com

docs.intersystems.com

docs.janusgraph.org

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Sachin Sinha, BangDB

InterSystems

Linux Foundation; originally developed as Titan by Aurelius

OpenSource, formerly Basho Technologies

Initial release

2012

1997

2017

2009

Current release

BangDB 2.0, October 2021

2018.1.4, May 2020

0.6.3, February 2023

3.2.0, December 2022

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

Erlang

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
OS X

Data scheme

schema-free

depending on used data model

yes

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

restricted

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API
Native Erlang Interface

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Java

Clojure
Java
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

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

none

yes

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

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

selectable replication factor

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

links between data sets can be stored

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

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)

Access rights for users, groups and roles

User authentification and security via Rexster Graph Server

yes, using Riak Security

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