DBMS > Blueflood vs. CockroachDB vs. Dragonfly vs. FatDB vs. SQLite

System Properties Comparison Blueflood vs. CockroachDB vs. Dragonfly vs. FatDB vs. SQLite

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

Document store
Key-value store

Relational DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

blueflood.io

www.cockroachlabs.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.sqlite.org

Technical documentation

github.com/rax-maas/blueflood/wiki

www.cockroachlabs.com/docs

www.dragonflydb.io/docs

www.sqlite.org/docs.html

Developer

Rackspace

Cockroach Labs

DragonflyDB team and community contributors

FatCloud

Dwayne Richard Hipp

Initial release

2013

2015

2023

2012

2000

Current release

24.1.0, May 2024

1.0, March 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0, commercial license available

Open Source

BSL 1.1

commercial

Open Source

Public Domain

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

C++

Server operating systems

Linux
OS X

Linux
macOS
Windows

Linux

Windows

server-less

Data scheme

predefined scheme

dynamic schema

scheme-free

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

not rigid because of 'dynamic typing' concept.

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

yes, wire compatible with PostgreSQL

Via inetgration in SQL Server

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP REST

JDBC

Proprietary protocol

RESP - REdis Serialization Protocol

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Lua

yes

via applications

Triggers

publish/subscribe channels provide some trigger functionality

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication using RAFT

Source-replica replication

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

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

via file-system locks

Durability

Support for making data persistent

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

Role-based access control

Password-based authentication

Can implement custom security layer via applications

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