DBMS > 4D vs. BigObject vs. jBASE vs. SiteWhere vs. Vitess

System Properties Comparison 4D vs. BigObject vs. jBASE vs. SiteWhere vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Analytic DBMS for real-time computations and queries

A robust multi-value DBMS comprising development tools and middleware

M2M integration platform for persisting/querying time series data

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Multivalue DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

www.4d.com

bigobject.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

github.com/sitewhere/sitewhere

vitess.io

Technical documentation

developer.4d.com

docs.bigobject.io

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

sitewhere1.sitewhere.io/index.html

vitess.io/docs

Developer

4D, Inc

BigObject, Inc.

Rocket Software (formerly Zumasys)

SiteWhere

The Linux Foundation, PlanetScale

Initial release

1984

2015

1991

2010

2013

Current release

v20, April 2023

5.7

15.0.2, December 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Common Public Attribution License Version 1.0

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

Server operating systems

OS X
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

AIX
Linux
Windows

Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

yes

schema-free

predefined scheme

yes

Typing

predefined data types such as float or date

yes

optional

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-like DML and DDL statements

Embedded SQL for jBASE in BASIC

yes

with proprietary extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP REST

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

4D proprietary IDE
PHP

.Net
Basic
Jabbascript
Java

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

Lua

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

selectable replication factor

based on HBase

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

none

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Access rights can be defined down to the item level

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

SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

Ten Popular IoT Platforms You Should be Aware of
27 March 2023, Open Source For You

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

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

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

PlanetScale Serves up Vitess-Powered Serverless MySQL
23 November 2021, The New Stack

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

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News

Share this page