DBMS > 4D vs. Apache Druid vs. gStore vs. Vitess

System Properties Comparison 4D vs. Apache Druid vs. gStore vs. Vitess

Please select another system to include it in the comparison.

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 native Graph DBMS to store and maintain very large RDF datasets.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	0.86
Rank	#202	Overall
	#95	Relational DBMS

Website

Technical documentation

developer.4d.com

druid.apache.org/docs/latest/design

en.gstore.cn/#/enDocs

vitess.io/docs

Developer

4D, Inc

Apache Software Foundation and contributors

The Linux Foundation, PlanetScale

Initial release

1984

2012

2016

2013

Current release

v20, April 2023

30.0.0, June 2024

1.2, November 2023

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

BSD

Open Source

Apache Version 2.0, commercial licenses 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

Java

C++

Server operating systems

OS X
Windows

Linux
OS X
Unix

Linux

Docker
Linux
macOS

Data scheme

yes

schema-less columns are supported

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

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

with proprietary extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
RESTful HTTP/JSON API

HTTP API
SPARQL 1.1

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

4D proprietary IDE
PHP

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Imply Announces the Availability of Imply Polaris, a Database-as-a-Service Built from Apache Druid, on Microsoft Azure
26 June 2024, businesswire.com

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Apache® Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers’ Choice Awards
26 January 2024, businesswire.com

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

provided by Google News

Deepthi Sigireddi on Distributed Database Architecture in the Cloud Native Era
20 May 2024, InfoQ.com

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale offers undo button to reverse schema migration without losing data
24 March 2022, The Register

CNCF’s Vitess Scales MySQL with the Help of Kubernetes
9 February 2018, The New Stack

provided by Google News

Share this page