DBMS > 4D vs. PostGIS vs. Sequoiadb vs. TimescaleDB vs. Vitess

System Properties Comparison 4D vs. PostGIS vs. Sequoiadb vs. TimescaleDB vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Spatial extension of PostgreSQL

NewSQL database with distributed OLTP and SQL

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Spatial DBMS

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

Technical documentation

developer.4d.com

postgis.net/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.timescale.com

vitess.io/docs

Developer

4D, Inc

Sequoiadb Ltd.

Timescale

The Linux Foundation, PlanetScale

Initial release

1984

2005

2013

2017

2013

Current release

v20, April 2023

3.4.2, February 2024

2.15.0, May 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

GPL v2.0

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache 2.0

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

C++

Server operating systems

OS X
Windows

Linux

Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

SQL-like query language

yes

full PostgreSQL SQL syntax

yes

with proprietary extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

proprietary protocol using JSON

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

4D proprietary IDE
PHP

.Net
C++
Java
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

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

user defined functions

JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

based on PostgreSQL

Sharding

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

based on PostgreSQL

Source-replica replication

Source-replica replication with hot standby and reads on replicas

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

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

Document is locked during a transaction

ACID

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

yes

based on PostgreSQL

simple password-based access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

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More resources

DB-Engines blog posts

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

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News

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18 May 2021, Datanami

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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

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