DBMS > Amazon DynamoDB vs. Datomic vs. IBM Db2 warehouse vs. Quasardb vs. SAP SQL Anywhere

System Properties Comparison Amazon DynamoDB vs. Datomic vs. IBM Db2 warehouse vs. Quasardb vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Cloud-based data warehousing service

Distributed, high-performance timeseries database

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational 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	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

aws.amazon.com/dynamodb

www.datomic.com

www.ibm.com/products/db2/warehouse

quasar.ai

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.aws.amazon.com/dynamodb

docs.datomic.com

doc.quasar.ai/master

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Amazon

Cognitect

IBM

quasardb

SAP

formerly Sybase

Initial release

2012

2014

2009

1992

Current release

1.0.7075, December 2023

3.14.1, January 2024

17, July 2015

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

limited edition free

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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, Clojure

C++

Server operating systems

hosted

All OS with a Java VM

hosted

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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.

Import/export of XML data possible

yes

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

PL/SQL, SQL PL

yes, in C/C++, Java, .Net or Perl

Triggers

yes

by integration with AWS Lambda

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

yes

Source-replica replication with selectable replication factor

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

Transient mode

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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