DBMS > Ehcache vs. IBM Cloudant vs. IRONdb vs. Microsoft Azure Cosmos DB vs. TigerGraph

System Properties Comparison Ehcache vs. IBM Cloudant vs. IRONdb vs. Microsoft Azure Cosmos DB vs. TigerGraph

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A widely adopted Java cache with tiered storage options

Database as a Service offering based on Apache CouchDB

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Key-value store

Document store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

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

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.ehcache.org

www.ibm.com/products/cloudant

www.circonus.com/solutions/time-series-database/

azure.microsoft.com/services/cosmos-db

www.tigergraph.com

Technical documentation

www.ehcache.org/documentation

cloud.ibm.com/docs/Cloudant

docs.circonus.com/irondb/category/getting-started

learn.microsoft.com/azure/cosmos-db

docs.tigergraph.com

Developer

Terracotta Inc, owned by Software AG

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Circonus LLC.

Microsoft

Initial release

2009

2010

2017

2014

2017

Current release

3.10.0, March 2022

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

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

C and C++

C++

Server operating systems

All OS with a Java VM

hosted

Linux

hosted

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

JCache

RESTful HTTP/JSON API

HTTP API

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

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

Supported programming languages

Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

C++
Java

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes, in Lua

JavaScript

yes

Triggers

yes

Cache Event Listeners

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Automatic, metric affinity per node

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware

yes

Implicit feature of the cloud service

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

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

supports JTA and can work as an XA resource

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

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

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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