DBMS > Blueflood vs. DataFS vs. Elasticsearch vs. OrigoDB

System Properties Comparison Blueflood vs. DataFS vs. Elasticsearch vs. OrigoDB

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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.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A fully ACID in-memory object graph database

Primary database model

Time Series DBMS

Object oriented DBMS

Search engine

Document store
Object oriented DBMS

Secondary database models

Graph DBMS

Document store
Spatial DBMS
Vector 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	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

blueflood.io

newdatabase.com

www.elastic.co/elasticsearch

origodb.com

Technical documentation

github.com/rax-maas/blueflood/wiki

dev.mobiland.com/Overview.xsp

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

origodb.com/docs

Developer

Rackspace

Mobiland AG

Elastic

Robert Friberg et al

Initial release

2013

2018

2010

2009

under the name LiveDB

Current release

1.1.263, October 2022

8.6, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Elastic License

Open Source

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

Server operating systems

Linux
OS X

Windows

All OS with a Java VM

Linux
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

Flexible type definitions. Once a type is defined, it is persistent

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP REST

.NET Client API
Proprietary client DLL
WinRT client

Java API
RESTful HTTP/JSON API

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net
C
C#
C++
VB.Net

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net

Server-side scripts

Stored procedures

yes

Triggers

no, except callback-events from server when changes happened

yes

by using the 'percolation' feature

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Proprietary Sharding system

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

Windows-Profile

Role based authorization

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