DBMS > 4D vs. Apache Impala vs. Apache Pinot vs. Kyligence Enterprise

System Properties Comparison 4D vs. Apache Impala vs. Apache Pinot vs. Kyligence Enterprise

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Analytic DBMS for Hadoop

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Primary database model

Relational DBMS

Secondary database models

Document store

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	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Website

www.4d.com

impala.apache.org

pinot.apache.org

kyligence.io/kyligence-enterprise

Technical documentation

developer.4d.com

impala.apache.org/impala-docs.html

docs.pinot.apache.org

Developer

4D, Inc

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation and contributors

Kyligence, Inc.

Initial release

1984

2013

2015

2016

Current release

v20, April 2023

4.1.0, June 2022

1.0.0, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

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++

Java

Server operating systems

OS X
Windows

Linux

All OS with a Java JDK11 or higher

Linux

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-like DML and DDL statements

SQL-like query language

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

JDBC

JDBC
ODBC
RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

Go
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

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

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

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.

User concepts

Access control

Users and groups

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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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
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