DBMS > Dragonfly vs. NCache vs. NSDb vs. RocksDB vs. SwayDB

System Properties Comparison Dragonfly vs. NCache vs. NSDb vs. RocksDB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

Open-Source and Enterprise in-memory Key-Value Store

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Key-value store

Time Series DBMS

Key-value store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

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

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

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

www.alachisoft.com/ncache

nsdb.io

rocksdb.org

swaydb.simer.au

Technical documentation

www.dragonflydb.io/docs

www.alachisoft.com/resources/docs

nsdb.io/Architecture

github.com/facebook/rocksdb/wiki

Developer

DragonflyDB team and community contributors

Alachisoft

Facebook, Inc.

Simer Plaha

Initial release

2023

2005

2017

2013

2018

Current release

1.0, March 2023

5.3.3, April 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Enterprise Edition available

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

GNU Affero GPL V3.0

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

C++

C#, .NET, .NET Core, Java

Java, Scala

C++

Scala

Server operating systems

Linux

Linux
Windows

Linux
macOS

Linux

Data scheme

scheme-free

schema-free

Typing

predefined data types such as float or date

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

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

IDistributedCache
JCache
LINQ
Proprietary native API

gRPC
HTTP REST
WebSocket

C++ API
Java 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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Java
Scala

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Lua

support for stored procedures with SQL-Server CLR

Triggers

publish/subscribe channels provide some trigger functionality

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, with selectable consistency level

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

optimistic locking and pessimistic locking

yes

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.