DBMS > Dragonfly vs. HyperSQL vs. Newts vs. SAP IQ

System Properties Comparison Dragonfly vs. HyperSQL vs. Newts vs. SAP IQ

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Time Series DBMS based on Cassandra

Columnar RDBMS optimized for Big Data analytics

Primary database model

column-oriented

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

Score	0.42
Rank	#271	Overall
	#38	Key-value stores

Score	3.90
Rank	#85	Overall
	#46	Relational DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Website

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

hsqldb.org

opennms.github.io/newts

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

www.dragonflydb.io/docs

hsqldb.org/web/hsqlDocsFrame.html

github.com/OpenNMS/newts/wiki

help.sap.com/docs/SAP_IQ

Developer

DragonflyDB team and community contributors

OpenNMS Group

SAP, formerly Sybase

Initial release

2023

2001

2014

1994

Current release

1.0, March 2023

2.7.2, June 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

based on BSD license

Open Source

Apache 2.0

commercial

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

Server operating systems

Linux

All OS with a Java VM

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

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

scheme-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP REST
Java API

ADO.NET
JDBC
ODBC
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

All languages supporting JDBC/ODBC
Java

Java

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

Java, SQL

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

selectable replication factor

based on Cassandra

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

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

Atomic execution of command blocks and scripts

ACID

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

fine grained access rights according to SQL-standard

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