DBMS > Microsoft Azure Cosmos DB vs. Newts vs. Quasardb vs. Sequoiadb vs. Yaacomo

System Properties Comparison Microsoft Azure Cosmos DB vs. Newts vs. Quasardb vs. Sequoiadb vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

NewSQL database with distributed OLTP and SQL

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

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

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

opennms.github.io/newts

quasar.ai

www.sequoiadb.com

yaacomo.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Microsoft

OpenNMS Group

quasardb

Sequoiadb Ltd.

Q2WEB GmbH

Initial release

2014

2009

2013

2009

Current release

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Server: AGPL; Client: Apache V2

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

C++

Server operating systems

hosted

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux

Android
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

yes

oid, date, timestamp, binary, regex

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

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

HTTP REST
Java API

HTTP API

proprietary protocol using JSON

JDBC
ODBC

Supported programming languages

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

Java

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

consistent hashing

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

simple password-based access control

fine grained access rights according to SQL-standard

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