DBMS > 4D vs. Apache Druid vs. Dragonfly vs. Snowflake vs. Valentina Server

System Properties Comparison 4D vs. Apache Druid vs. Dragonfly vs. Snowflake vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Cloud-based data warehousing service for structured and semi-structured data

Object-relational database and reports server

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.4d.com

druid.apache.org

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

www.snowflake.com

www.valentina-db.net

Technical documentation

developer.4d.com

druid.apache.org/docs/latest/design

www.dragonflydb.io/docs

docs.snowflake.net/manuals/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

4D, Inc

Apache Software Foundation and contributors

DragonflyDB team and community contributors

Snowflake Computing Inc.

Paradigma Software

Initial release

1984

2012

2023

2014

1999

Current release

v20, April 2023

29.0.1, April 2024

1.0, March 2023

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

OS X
Windows

Linux
OS X
Unix

Linux

hosted

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

scheme-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL for querying

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protocol

CLI Client
JDBC
ODBC

ODBC

Supported programming languages

4D proprietary IDE
PHP

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

JavaScript (Node.js)
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Lua

user defined functions

yes

Triggers

yes

publish/subscribe channels provide some trigger functionality

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, via HDFS, S3 or other storage engines

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

Users and groups

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Password-based authentication

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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