DBMS > 4D vs. PouchDB vs. SQLite vs. Vertica vs. VoltDB

System Properties Comparison 4D vs. PouchDB vs. SQLite vs. Vertica vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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Trend Chart

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

developer.4d.com

pouchdb.com/guides

www.sqlite.org/docs.html

vertica.com/documentation

docs.voltdb.com

Developer

4D, Inc

Apache Software Foundation

Dwayne Richard Hipp

OpenText

previously Micro Focus and Hewlett Packard

VoltDB Inc.

Initial release

1984

2012

2000

2005

2010

Current release

v20, April 2023

7.1.1, June 2019

3.46.0 (23 May 2024), May 2024

12.0.3, January 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Public Domain

commercial

Limited community edition free

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

Java, C++

Server operating systems

OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Linux

Linux
OS X

for development

Data scheme

yes

schema-free

yes

dynamic column types

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

via views

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

yes

close to SQL 92

yes

SQL-92 is not fully supported

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

yes

only a subset of SQL 99

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

4D proprietary IDE
PHP

JavaScript

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#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes, PostgreSQL PL/pgSQL, with minor differences

Java

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

horizontal partitioning, hierarchical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

Snapshots and command logging

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
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