DBMS > Dragonfly vs. Hyprcubd vs. Interbase vs. Microsoft Azure Table Storage vs. Microsoft SQL Server

System Properties Comparison Dragonfly vs. Hyprcubd vs. Interbase vs. Microsoft Azure Table Storage vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Hyprcubd 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

Serverless Time Series DBMS

Light-weight proven RDBMS

originally from Borland

A Wide Column Store for rapid development using massive semi-structured datasets

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

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

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

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

hyprcubd.com (offline)

www.embarcadero.com/products/interbase

azure.microsoft.com/en-us/services/storage/tables

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

Technical documentation

www.dragonflydb.io/docs

docs.embarcadero.com/products/interbase

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

Developer

DragonflyDB team and community contributors

Hyprcubd, Inc.

Embarcadero

Microsoft

Initial release

2023

1984

2012

1989

Current release

1.0, March 2023

InterBase 2020, December 2019

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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

hosted

Android
iOS
Linux
OS X
Windows

hosted

Linux
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

time, int, uint, float, string

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.

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

gRPC (https)

ADO.NET
JDBC
ODBC

RESTful HTTP API

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

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
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

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

Server-side scripts

Stored procedures

Lua

yes

Interbase procedure and trigger language

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

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Interbase Change Views

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Multiversion concurreny control

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

token access

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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