DBMS > Dragonfly vs. Hypertable vs. SAP HANA vs. SAP SQL Anywhere vs. UniData,UniVerse

System Properties Comparison Dragonfly vs. Hypertable vs. SAP HANA vs. SAP SQL Anywhere vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed 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

An open source BigTable implementation based on distributed file systems such as Hadoop

In-memory, column based data store. Available as appliance or cloud service

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

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

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

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

www.sap.com/products/hana.html

www.sap.com/products/technology-platform/sql-anywhere.html

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

www.dragonflydb.io/docs

help.sap.com/hana

help.sap.com/docs/SAP_SQL_Anywhere

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

DragonflyDB team and community contributors

Hypertable Inc.

SAP

formerly Sybase

Rocket Software

Initial release

2023

2009

2010

1992

1985

Current release

1.0, March 2023

0.9.8.11, March 2016

2.0 SPS07 (April 4, 2023), April 2023

17, July 2015

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

GNU version 3. Commercial license available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

scheme-free

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

optional

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

C++ API
Thrift

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based 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
Perl
PHP
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

Lua

SQLScript, R

yes, in C/C++, Java, .Net or Perl

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor on file system level

yes

Source-replica replication

Database mirroring

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

configurable

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

yes

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

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