DBMS > Dragonfly vs. Hive vs. HyperSQL vs. NCache vs. ToroDB

System Properties Comparison Dragonfly vs. Hive vs. HyperSQL vs. NCache vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

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	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

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

Website

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

hive.apache.org

hsqldb.org

www.alachisoft.com/ncache

github.com/torodb/server

Technical documentation

www.dragonflydb.io/docs

cwiki.apache.org/confluence/display/Hive/Home

hsqldb.org/web/hsqlDocsFrame.html

www.alachisoft.com/resources/docs

Developer

DragonflyDB team and community contributors

Apache Software Foundation

initially developed by Facebook

Alachisoft

8Kdata

Initial release

2023

2012

2001

2005

2016

Current release

1.0, March 2023

3.1.3, April 2022

2.7.2, June 2023

5.3.3, April 2024

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache Version 2

Open Source

based on BSD license

Open Source

Enterprise Edition available

Open Source

AGPL-V3

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++

Java

C#, .NET, .NET Core, Java

Java

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

All OS with a Java 7 VM

Data scheme

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

partial

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

yes

string, integer, double, boolean, date, object_id

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

SQL-like DML and DDL statements

yes

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

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Thrift

HTTP API

JDBC via HTTP
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native 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++
Java
PHP
Python

All languages supporting JDBC/ODBC
Java

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

Server-side scripts

Stored procedures

Lua

yes

user defined functions and integration of map-reduce

Java, SQL

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

Sharding

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

none

yes, with selectable consistency level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

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

Eventual Consistency
Immediate Consistency

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

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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

Access rights for users and roles

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.

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