DBMS > Amazon DocumentDB vs. InterSystems Caché vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. TDengine

System Properties Comparison Amazon DocumentDB vs. InterSystems Caché vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. TDengine

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

A multi-model DBMS and application server

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS and big data platform

Primary database model

Document store

Key-value store
Object oriented DBMS
Relational DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Document store

Spatial DBMS

Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

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

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

aws.amazon.com/documentdb

www.intersystems.com/products/cache

janusgraph.org

azure.microsoft.com/services/cosmos-db

github.com/taosdata/TDengine
tdengine.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.intersystems.com

docs.janusgraph.org

learn.microsoft.com/azure/cosmos-db

docs.tdengine.com

Developer

InterSystems

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

TDEngine, previously Taos Data

Initial release

2019

1997

2017

2014

2019

Current release

2018.1.4, May 2020

0.6.3, February 2023

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

AGPL V3, also commercial editions available

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

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

hosted

Linux
Windows

Data scheme

schema-free

depending on used data model

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

Standard SQL with extensions for time-series applications

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

.NET Client API
JDBC
ODBC
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

JDBC
RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
Java

Clojure
Java
Python

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

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Source-replica replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Faunus, a graph analytics engine

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Relationships in graphs

Transaction concepts

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

Atomic single-document operations

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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 and roles

Access rights for users, groups and roles

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

yes

More information provided by the system vendor

Specific characteristics

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Market metrics

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Licensing and pricing models

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