DBMS > Amazon DynamoDB vs. Galaxybase vs. MySQL vs. Splice Machine vs. TimesTen

System Properties Comparison Amazon DynamoDB vs. Galaxybase vs. MySQL vs. Splice Machine vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Scalable, ACID-compliant native distributed parallel graph platform

Widely used open source RDBMS

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Document store
Key-value store

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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	0.00
Rank	#385	Overall
	#40	Graph DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

aws.amazon.com/dynamodb

galaxybase.com

www.mysql.com

splicemachine.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.aws.amazon.com/dynamodb

dev.mysql.com/doc

splicemachine.com/how-it-works

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Amazon

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Oracle

since 2010, originally MySQL AB, then Sun

Splice Machine

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2017

1995

2014

1998

Current release

Nov 20, November 2021

9.0.0, July 2024

3.1, March 2021

Release 22.1

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL 3.0, commercial license available

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

C and Java

C and C++

Java

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free

Strong typed schema

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
Native Spark Datasource
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

user defined procedures and functions

yes

proprietary syntax

yes

Java

PL/SQL

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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)

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

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

fine grained access rights according to SQL-standard

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