DBMS > 4D vs. FeatureBase vs. Kyligence Enterprise vs. VoltDB

System Properties Comparison 4D vs. FeatureBase vs. Kyligence Enterprise vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

A distributed analytics engine for big data, built on top of Apache Kylin

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

Relational DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.4d.com

www.featurebase.com

kyligence.io/kyligence-enterprise

www.voltdb.com

Technical documentation

developer.4d.com

docs.featurebase.com

docs.voltdb.com

Developer

4D, Inc

Molecula and Pilosa Open Source Contributors

Kyligence, Inc.

VoltDB Inc.

Initial release

1984

2017

2016

2010

Current release

v20, April 2023

2022, May 2022

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

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

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

Java, C++

Server operating systems

OS X
Windows

Linux
macOS

Linux

Linux
OS X

for development

Data scheme

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 queries

ANSI SQL for queries (using Apache Calcite)

yes

only a subset of SQL 99

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

4D proprietary IDE
PHP

Java
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

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2 March 2016, Paul Andlinger

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