DBMS > 4D vs. Apache Impala vs. Bangdb

System Properties Comparison 4D vs. Apache Impala vs. Bangdb

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Analytic DBMS for Hadoop

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series 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	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Website

www.4d.com

impala.apache.org

bangdb.com

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

Sachin Sinha, BangDB

Initial release

1984

2013

2012

Current release

v20, April 2023

4.1.0, June 2022

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

BSD 3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, C++

Server operating systems

OS X
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

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

SQL

Support of SQL

yes

close to SQL 92

SQL-like DML and DDL statements

SQL like support with command line tool

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

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

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

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Tunable consistency, set CAP knob accordingly

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

In-memory capabilities

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

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

yes (enterprise version only)

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More resources

DB-Engines blog posts

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Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

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