DBMS > HBase vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. RRDtool vs. TigerGraph

System Properties Comparison HBase vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. RRDtool vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Database as a Service offering based on Apache CouchDB

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.

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Wide column store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.14
Rank	#124	Overall
	#10	Time Series DBMS

Score	1.83
Rank	#141	Overall
	#13	Graph DBMS

Website

hbase.apache.org

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

oss.oetiker.ch/rrdtool

www.tigergraph.com

Technical documentation

hbase.apache.org/book.html

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

oss.oetiker.ch/rrdtool/doc

docs.tigergraph.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Tobias Oetiker

Initial release

2008

2010

2014

1999

2017

Current release

2.3.4, January 2021

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

GPL V2 and FLOSS

commercial

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

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

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

hosted

HP-UX
Linux

Linux

Data scheme

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

JSON types

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

Java API
RESTful HTTP API
Thrift

RESTful HTTP/JSON API

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

in-process shared library
Pipes

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

.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

C++
Java

Server-side scripts

Stored procedures

yes

Coprocessors in Java

View functions (Map-Reduce) in JavaScript

JavaScript

yes

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

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*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Single row ACID (across millions of columns)

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

by using the rrdcached daemon

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users can be defined per database

Access rights can be defined down to the item level

Role-based access control

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