DBMS > 4D vs. Apache Impala vs. atoti vs. Kdb vs. Newts

System Properties Comparison 4D vs. Apache Impala vs. atoti vs. Kdb vs. Newts

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Analytic DBMS for Hadoop

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

High performance Time Series DBMS

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

Object oriented DBMS

Time Series DBMS
Vector DBMS

Time Series DBMS

Secondary database models

Document store

Relational 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	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

opennms.github.io/newts

Technical documentation

developer.4d.com

impala.apache.org/impala-docs.html

docs.atoti.io

code.kx.com

github.com/OpenNMS/newts/wiki

Developer

4D, Inc

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

ActiveViam

Kx Systems, a division of First Derivatives plc

OpenNMS Group

Initial release

1984

2013

2000

kdb was released 2000, kdb+ in 2003

2014

Current release

v20, April 2023

4.1.0, June 2022

3.6, May 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

free versions available

commercial

free 32-bit version

Open Source

Apache 2.0

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

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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

table attribute 'grouped'

SQL

Support of SQL

yes

close to SQL 92

SQL-like DML and DDL statements

Multidimensional Expressions (MDX)

SQL-like query language (q)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP REST
Java API

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Python

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

horizontal partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

Users and groups

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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