DBMS > atoti vs. Hawkular Metrics vs. IBM Cloudant vs. LevelDB

System Properties Comparison atoti vs. Hawkular Metrics vs. IBM Cloudant vs. LevelDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Database as a Service offering based on Apache CouchDB

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Primary database model

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Website

atoti.io

www.hawkular.org

www.ibm.com/products/cloudant

github.com/google/leveldb

Technical documentation

docs.atoti.io

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

cloud.ibm.com/docs/Cloudant

github.com/google/leveldb/blob/main/doc/index.md

Developer

ActiveViam

Community supported by Red Hat

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Google

Initial release

2014

2010

2011

Current release

1.23, February 2021

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

C++

Server operating systems

Linux
OS X
Windows

hosted

Illumos
Linux
OS X
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

APIs and other access methods

HTTP REST

RESTful HTTP/JSON API

Supported programming languages

Go
Java
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

Python

View functions (Map-Reduce) in JavaScript

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users can be defined per database

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