DBMS > Amazon DynamoDB vs. Blueflood vs. Datomic vs. Infobright vs. Microsoft Azure Cosmos DB

System Properties Comparison Amazon DynamoDB vs. Blueflood vs. Datomic vs. Infobright vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Scalable TimeSeries DBMS based on Cassandra

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

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

Website

aws.amazon.com/dynamodb

blueflood.io

www.datomic.com

ignitetech.com/softwarelibrary/infobrightdb

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/rax-maas/blueflood/wiki

docs.datomic.com

learn.microsoft.com/azure/cosmos-db

Developer

Amazon

Rackspace

Cognitect

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

Initial release

2012

2013

2012

2005

2014

Current release

1.0.6735, June 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

limited edition free

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Java, Clojure

Server operating systems

hosted

Linux
OS X

All OS with a Java VM

Linux
Windows

hosted

Data scheme

schema-free

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

Knowledge Grid Technology used instead

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

HTTP REST

RESTful HTTP API

ADO.NET
JDBC
ODBC

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

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

yes

Transaction Functions

JavaScript

Triggers

yes

by integration with AWS Lambda

By using transaction functions

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

But extensive use of caching in the application peers

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

none

But extensive use of caching in the application peers

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights can be defined down to the item level

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