DBMS > Dragonfly vs. InterSystems IRIS vs. Spark SQL vs. SQLite vs. STSdb

System Properties Comparison Dragonfly vs. InterSystems IRIS vs. Spark SQL vs. SQLite vs. STSdb

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

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Key-value store

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

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

Score	3.54
Rank	#84	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

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

www.intersystems.com/products/intersystems-iris

spark.apache.org/sql

www.sqlite.org

github.com/STSSoft/STSdb4

Technical documentation

www.dragonflydb.io/docs

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

Developer

DragonflyDB team and community contributors

InterSystems

Apache Software Foundation

Dwayne Richard Hipp

STS Soft SC

Initial release

2023

2018

2014

2000

2011

Current release

1.0, March 2023

2023.3, June 2023

3.5.0 ( 2.13), September 2023

3.46.0 (23 May 2024), May 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

GPLv2, commercial license available

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++

Scala

Server operating systems

Linux

AIX
Linux
macOS
Ubuntu
Windows

Linux
OS X
Windows

server-less

Windows

Data scheme

scheme-free

depending on used data model

yes

dynamic column types

yes

Typing

predefined data types such as float or date

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

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.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

.Net
C++
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C#
Java

Server-side scripts

Stored procedures

Lua

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

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

via file-system locks

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

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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