DBMS > Heroic vs. IBM Cloudant vs. Kingbase vs. Microsoft Azure Cosmos DB vs. RRDtool

System Properties Comparison Heroic vs. IBM Cloudant vs. Kingbase vs. Microsoft Azure Cosmos DB vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Database as a Service offering based on Apache CouchDB

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Globally distributed, horizontally scalable, multi-model database service

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Time Series DBMS

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

github.com/spotify/heroic

www.ibm.com/products/cloudant

www.kingbase.com.cn

azure.microsoft.com/services/cosmos-db

oss.oetiker.ch/rrdtool

Technical documentation

spotify.github.io/heroic

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

oss.oetiker.ch/rrdtool/doc

Developer

Spotify

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

BeiJing KINGBASE Information technologies inc.

Microsoft

Tobias Oetiker

Initial release

2014

2010

1999

2014

1999

Current release

V8.0, August 2021

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL V2 and FLOSS

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 and Java

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux
Windows

hosted

HP-UX
Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

via Elasticsearch

yes

All properties auto-indexed by default

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP/JSON API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

in-process shared library
Pipes

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

by using the rrdcached daemon

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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