DBMS > Amazon DynamoDB vs. GeoSpock vs. mSQL vs. Sadas Engine vs. Sphinx

System Properties Comparison Amazon DynamoDB vs. GeoSpock vs. mSQL vs. Sadas Engine vs. Sphinx

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Primary database model

Document store
Key-value store

Relational DBMS

Search engine

Secondary database models

Time Series 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	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

aws.amazon.com/dynamodb

geospock.com

hughestech.com.au/products/msql

www.sadasengine.com

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/dynamodb

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

sphinxsearch.com/docs

Developer

Amazon

GeoSpock

Hughes Technologies

SADAS s.r.l.

Sphinx Technologies Inc.

Initial release

2012

1994

2006

2001

Current release

2.0, September 2019

4.4, October 2021

8.0

3.5.1, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free licenses can be provided

commercial

free trial version available

Open Source

GPL version 2, commercial licence available

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, Javascript

C++

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

AIX
Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

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

temporal, categorical

yes

full-text index on all search fields

SQL

Support of SQL

ANSI SQL for query only (using Presto)

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

JDBC

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Immediate Consistency

none

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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'

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 can be defined per table

Access rights for users, groups and roles according to SQL-standard

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