DBMS > Dragonfly vs. InterSystems Caché vs. Microsoft SQL Server vs. NSDb vs. STSdb

System Properties Comparison Dragonfly vs. InterSystems Caché vs. Microsoft SQL Server vs. NSDb vs. STSdb

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore 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

A multi-model DBMS and application server

Microsofts flagship relational DBMS

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Document store

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	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

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

www.intersystems.com/products/cache

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

nsdb.io

github.com/STSSoft/STSdb4

Technical documentation

www.dragonflydb.io/docs

docs.intersystems.com

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

nsdb.io/Architecture

Developer

DragonflyDB team and community contributors

InterSystems

Microsoft

STS Soft SC

Initial release

2023

1997

1989

2017

2011

Current release

1.0, March 2023

2018.1.4, May 2020

SQL Server 2022, November 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java, Scala

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
macOS

Windows

Data scheme

scheme-free

depending on used data model

yes

Typing

predefined data types such as float or date

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

yes

yes: int, bigint, decimal, string

yes

primitive types and user defined types (classes)

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

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

.NET Client API
JDBC
ODBC
RESTful HTTP API

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

gRPC
HTTP REST
WebSocket

.NET Client 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#
C++
Java

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

Java
Scala

C#
Java

Server-side scripts

Stored procedures

Lua

yes

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

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual 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

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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