DBMS > 4D vs. atoti vs. Cachelot.io vs. Hawkular Metrics vs. LeanXcale

System Properties Comparison 4D vs. atoti vs. Cachelot.io vs. Hawkular Metrics vs. LeanXcale

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

In-memory caching system

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Key-value 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	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Website

Technical documentation

developer.4d.com

docs.atoti.io

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

Developer

4D, Inc

ActiveViam

Community supported by Red Hat

LeanXcale

Initial release

1984

2015

2014

2015

Current release

v20, April 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Simplified BSD License

Open Source

Apache 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

Java

C++

Java

Server operating systems

OS X
Windows

FreeBSD
Linux
OS X

Linux
OS X
Windows

Data scheme

yes

schema-free

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

Multidimensional Expressions (MDX)

yes

through Apache Derby

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Memcached protocol

HTTP REST

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

4D proprietary IDE
PHP

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Go
Java
Python
Ruby

C
Java
Scala

Server-side scripts

Stored procedures

yes

Python

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

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More resources

DB-Engines blog posts

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Recent citations in the news

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