DBMS > Blueflood vs. CouchDB vs. JanusGraph vs. Snowflake vs. ToroDB

System Properties Comparison Blueflood vs. CouchDB vs. JanusGraph vs. Snowflake vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A Graph DBMS optimized for distributed clusters

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

Cloud-based data warehousing service for structured and semi-structured data

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

github.com/torodb/server

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.couchdb.org/en/stable

docs.janusgraph.org

docs.snowflake.net/manuals/index.html

Developer

Rackspace

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Linux Foundation; originally developed as Titan by Aurelius

Snowflake Computing Inc.

8Kdata

Initial release

2013

2005

2017

2014

2016

Current release

3.3.3, December 2023

0.6.3, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Java

Server operating systems

Linux
OS X

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

hosted

All OS with a Java 7 VM

Data scheme

predefined scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Clojure
Java
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

improved architecture with release 2.0

yes

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

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

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.

User concepts

Access control

Access rights for users can be defined per database

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles

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