DBMS > JanusGraph vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. Trino vs. Warp 10

System Properties Comparison JanusGraph vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. Trino vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering with high compatibility to Microsoft SQL Server

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

janusgraph.org

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/products/azure-sql/database

trino.io

www.warp10.io

Technical documentation

docs.janusgraph.org

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/en-us/azure/azure-sql

trino.io/broadcast
trino.io/docs/current

www.warp10.io/content/02_Getting_started

Social network pages

Developer

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Trino Software Foundation

SenX

Initial release

2017

2014

2010

2012

2020 rebranded from PrestoSQL

2015

Current release

0.6.3, February 2023

V12

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Unix
Windows

hosted

Linux
macOS

for devlopment

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

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

yes

depending on connected data-source

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

HTTP API
Jupyter
WebSocket

Supported programming languages

Clojure
Java
Python

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

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

Transact SQL

yes, depending on connected data-source

yes

WarpScript

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

Implicit feature of the cloud service

depending on connected data-source

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, with always 3 replicas available

depending on connected data-source

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

depending on connected data-source

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

depending on connected data-source

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

depending on connected data-source

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

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

SQL standard access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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