DBMS > Blueflood vs. DataFS vs. Datomic vs. RocksDB

System Properties Comparison Blueflood vs. DataFS vs. Datomic vs. RocksDB

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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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Graph DBMS

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

Technical documentation

github.com/rax-maas/blueflood/wiki

dev.mobiland.com/Overview.xsp

docs.datomic.com

github.com/facebook/rocksdb/wiki

Developer

Rackspace

Mobiland AG

Cognitect

Facebook, Inc.

Initial release

2013

2018

2012

2013

Current release

1.1.263, October 2022

1.0.7180, July 2024

9.4.0, June 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

Open Source

BSD

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

Java, Clojure

C++

Server operating systems

Linux
OS X

Windows

All OS with a Java VM

Linux

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)

yes

schema-free

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

SQL

Support of SQL

APIs and other access methods

HTTP REST

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

C++ API
Java API

Supported programming languages

.Net
C
C#
C++
VB.Net

Clojure
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

no, except callback-events from server when changes happened

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Proprietary Sharding system

none

But extensive use of caching in the application peers

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Windows-Profile

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