DBMS > Blueflood vs. Dragonfly vs. Microsoft SQL Server vs. RavenDB

System Properties Comparison Blueflood vs. Dragonfly vs. Microsoft SQL Server vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Microsofts flagship relational DBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

blueflood.io

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

www.microsoft.com/en-us/sql-server

ravendb.net

Technical documentation

github.com/rax-maas/blueflood/wiki

www.dragonflydb.io/docs

learn.microsoft.com/en-US/sql/sql-server

ravendb.net/docs

Developer

Rackspace

DragonflyDB team and community contributors

Microsoft

Hibernating Rhinos

Initial release

2013

2023

1989

2010

Current release

1.0, March 2023

SQL Server 2022, November 2022

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSL 1.1

commercial

restricted free version is available

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

Linux
OS X

Linux

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

predefined scheme

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (RQL)

APIs and other access methods

HTTP REST

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication

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

Eventual Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

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

Password-based authentication

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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