DBMS > atoti vs. Coveo vs. Microsoft Azure Cosmos DB vs. Newts vs. PostGIS

System Properties Comparison atoti vs. Coveo vs. Microsoft Azure Cosmos DB vs. Newts vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS based on Cassandra

Spatial extension of PostgreSQL

Primary database model

Object oriented DBMS

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	2.28
Rank	#114	Overall
	#11	Search engines

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

atoti.io

www.coveo.com

azure.microsoft.com/services/cosmos-db

opennms.github.io/newts

postgis.net

Technical documentation

docs.atoti.io

docs.coveo.com

learn.microsoft.com/azure/cosmos-db

github.com/OpenNMS/newts/wiki

postgis.net/documentation

Developer

ActiveViam

Coveo

Microsoft

OpenNMS Group

Initial release

2012

2014

2005

Current release

3.4.2, February 2024

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache 2.0

Open Source

GPL v2.0

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

Java

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

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

HTTP REST
Java API

Supported programming languages

C#
Java
JavaScript
Python

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

Java

Server-side scripts

Stored procedures

Python

JavaScript

user defined functions

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

yes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

based on Cassandra

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

granular access controls, API key management, content filters

Access rights can be defined down to the item level

yes

based on PostgreSQL

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