DBMS > Amazon DynamoDB vs. Atos Standard Common Repository vs. Blueflood vs. etcd vs. Microsoft Azure AI Search

System Properties Comparison Amazon DynamoDB vs. Atos Standard Common Repository vs. Blueflood vs. etcd vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

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

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Scalable TimeSeries DBMS based on Cassandra

A distributed reliable key-value store

Search-as-a-service for web and mobile app development

Primary database model

Document store
Key-value store

Time Series DBMS

Key-value store

Search engine

Secondary database models

Vector 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	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

Website

aws.amazon.com/dynamodb

atos.net/en/convergence-creators/portfolio/standard-common-repository

blueflood.io

etcd.io
github.com/etcd-io/etcd

azure.microsoft.com/en-us/services/search

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/rax-maas/blueflood/wiki

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

learn.microsoft.com/en-us/azure/search

Developer

Amazon

Atos Convergence Creators

Rackspace

Microsoft

Initial release

2012

2016

2013

2015

Current release

1703

3.4, August 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

Server operating systems

hosted

Linux

Linux
OS X

FreeBSD
Linux
Windows

experimental

hosted

Data scheme

schema-free

Schema and schema-less with LDAP views

predefined scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

LDAP

HTTP REST

gRPC
JSON over HTTP

RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages with LDAP bindings

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

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)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate 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

Atomic execution of specific operations

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.

yes

User concepts

Access control

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

LDAP bind authentication

yes

using Azure authentication

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