DBMS > Amazon DynamoDB vs. Ehcache vs. Sadas Engine vs. Sphinx vs. SwayDB

System Properties Comparison Amazon DynamoDB vs. Ehcache vs. Sadas Engine 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

A widely adopted Java cache with tiered storage options

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

www.ehcache.org/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

sphinxsearch.com/docs

Developer

Amazon

Terracotta Inc, owned by Software AG

SADAS s.r.l.

Sphinx Technologies Inc.

Simer Plaha

Initial release

2012

2009

2006

2001

2018

Current release

3.10.0, March 2022

8.0

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; commercial licenses available

commercial

free trial version available

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

AIX
Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

JCache

JDBC
ODBC
Proprietary protocol

Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

horizontal partitioning

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

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

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

supports JTA and can work as an XA resource

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

managed by 'Learn by Usage'

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 according to SQL-standard

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