DBMS > Blueflood vs. DataFS vs. LokiJS vs. Riak KV vs. Spark SQL

System Properties Comparison Blueflood vs. DataFS vs. LokiJS vs. Riak KV vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

In-memory JavaScript DBMS

Distributed, fault tolerant key-value store

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

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

Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

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

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

blueflood.io

newdatabase.com

github.com/techfort/LokiJS

spark.apache.org/sql

Technical documentation

github.com/rax-maas/blueflood/wiki

dev.mobiland.com/Overview.xsp

techfort.github.io/LokiJS

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

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Rackspace

Mobiland AG

OpenSource, formerly Basho Technologies

Apache Software Foundation

Initial release

2013

2018

2014

2009

2014

Current release

1.1.263, October 2022

3.2.0, December 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache version 2, commercial enterprise edition

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

Java

JavaScript

Erlang

Scala

Server operating systems

Linux
OS X

Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X

Linux
OS X
Windows

Data scheme

predefined scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

yes

Typing

predefined data types such as float or date

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

via views

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

.NET Client API
Proprietary client DLL
WinRT client

JavaScript API

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

JavaScript

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

Erlang

Triggers

no, except callback-events from server when changes happened

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Proprietary Sharding system

none

Sharding

no "single point of failure"

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Windows-Profile

yes, using Riak Security

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
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