DBMS > Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. OrientDB vs. Rockset vs. Spark SQL

System Properties Comparison Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. OrientDB vs. Rockset vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

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

Multi-model DBMS (Document, Graph, Key/Value)

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Document store
Graph DBMS
Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

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

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

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

orientdb.org

rockset.com

spark.apache.org/sql

Technical documentation

learn.microsoft.com/azure/cosmos-db

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

www.orientdb.com/docs/last/index.html

docs.rockset.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Microsoft

OrientDB LTD; CallidusCloud; SAP

Rockset

Apache Software Foundation

Initial release

2014

2010

2019

2014

Current release

V12

3.2.29, March 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

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

C++

Java

C++

Scala

Server operating systems

hosted

All OS with a Java JDK (>= JDK 6)

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

All properties auto-indexed by default

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language, no joins

Read-only SQL queries, including JOINs

SQL-like DML and DDL statements

APIs and other access methods

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

ADO.NET
JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP REST

JDBC
ODBC

Supported programming languages

.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

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

Go
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

JavaScript

Transact SQL

Java, Javascript

Triggers

JavaScript

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Automatic sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, with always 3 replicas available

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Access rights for users and organizations can be defined via Rockset console

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