DBMS > atoti vs. Google Cloud Bigtable vs. Microsoft Azure Cosmos DB vs. RethinkDB

System Properties Comparison atoti vs. Google Cloud Bigtable vs. Microsoft Azure Cosmos DB vs. RethinkDB

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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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Globally distributed, horizontally scalable, multi-model database service

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Object oriented DBMS

Key-value store
Wide column store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Secondary database models

Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

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

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

atoti.io

cloud.google.com/bigtable

azure.microsoft.com/services/cosmos-db

rethinkdb.com

Technical documentation

docs.atoti.io

cloud.google.com/bigtable/docs

learn.microsoft.com/azure/cosmos-db

rethinkdb.com/docs

Developer

ActiveViam

Google

Microsoft

The Linux Foundation

since July 2017

Initial release

2015

2014

2009

Current release

2.4.1, August 2020

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache Version 2

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

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

Supported programming languages

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

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

Python

JavaScript

Triggers

JavaScript

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

Multi-item ACID transactions with snapshot isolation within a partition

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

MVCC based

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights can be defined down to the item level

yes

users and table-level permissions

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