DBMS > Amazon DynamoDB vs. Hive vs. RethinkDB vs. Sphinx vs. SwayDB

System Properties Comparison Amazon DynamoDB vs. Hive vs. RethinkDB vs. Sphinx vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Open source search engine for searching in data from different sources, e.g. relational databases

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Key-value store

Secondary database models

Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

cwiki.apache.org/confluence/display/Hive/Home

rethinkdb.com/docs

sphinxsearch.com/docs

Developer

Amazon

Apache Software Foundation

initially developed by Facebook

The Linux Foundation

since July 2017

Sphinx Technologies Inc.

Simer Plaha

Initial release

2012

2009

2001

2018

Current release

3.1.3, April 2022

2.4.1, August 2020

3.5.1, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

GPL version 2, commercial licence available

Open Source

GNU Affero GPL V3.0

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

C++

Scala

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

full-text index on all search fields

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift

Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
PHP
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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

by integration with AWS Lambda

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

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 single-document operations

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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)

Access rights for users, groups and roles

yes

users and table-level permissions

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