DBMS > 4D vs. Apache Impala vs. Atos Standard Common Repository vs. Bangdb vs. Kyligence Enterprise

System Properties Comparison 4D vs. Apache Impala vs. Atos Standard Common Repository vs. Bangdb vs. Kyligence Enterprise

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Application development environment with integrated database management system

Analytic DBMS for Hadoop

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Converged and high performance database for device data, events, time series, document and graph

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

Primary database model

Relational DBMS

Document store
Key-value store

Document store
Graph 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	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Website

www.4d.com

impala.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

bangdb.com

kyligence.io/kyligence-enterprise

Technical documentation

developer.4d.com

impala.apache.org/impala-docs.html

docs.bangdb.com

Developer

4D, Inc

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

Sachin Sinha, BangDB

Kyligence, Inc.

Initial release

1984

2013

2016

2012

2016

Current release

v20, April 2023

4.1.0, June 2022

1703

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

BSD 3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C, C++

Java

Server operating systems

OS X
Windows

Linux

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like DML and DDL statements

SQL like support with command line tool

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

LDAP

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

All languages with LDAP bindings

C
C#
C++
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

yes

selectable replication factor, Knob for CAP (enterprise version only)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, run db with in-memory only mode

User concepts

Access control

Users and groups

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

LDAP bind authentication

yes (enterprise version only)

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More resources

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