DBMS > 4D vs. Apache Impala vs. Ehcache vs. Hawkular Metrics

System Properties Comparison 4D vs. Apache Impala vs. Ehcache vs. Hawkular Metrics

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Analytic DBMS for Hadoop

A widely adopted Java cache with tiered storage options

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Relational DBMS

Key-value store

Time Series 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	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Website

Technical documentation

developer.4d.com

impala.apache.org/impala-docs.html

www.ehcache.org/documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

4D, Inc

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Terracotta Inc, owned by Software AG

Community supported by Red Hat

Initial release

1984

2013

2009

2014

Current release

v20, April 2023

4.1.0, June 2022

3.10.0, March 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2; commercial licenses available

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

All OS with a Java VM

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

SQL

Support of SQL

yes

close to SQL 92

SQL-like DML and DDL statements

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

JCache

HTTP REST

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

Java

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Cache Event Listeners

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

yes

by using Terracotta Server

selectable replication factor

based on Cassandra

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 (Strong, Eventual, Weak)

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

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

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More resources

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