DBMS > Amazon DynamoDB vs. Greenplum vs. InfinityDB vs. Quasardb

System Properties Comparison Amazon DynamoDB vs. Greenplum vs. InfinityDB vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

A Java embedded Key-Value Store which extends the Java Map interface

Distributed, high-performance timeseries database

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Document store
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	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/dynamodb

greenplum.org

boilerbay.com

quasar.ai

Technical documentation

docs.aws.amazon.com/dynamodb

docs.greenplum.org

boilerbay.com/infinitydb/manual

doc.quasar.ai/master

Developer

Amazon

Pivotal Software Inc.

Boiler Bay Inc.

quasardb

Initial release

2012

2005

2002

2009

Current release

7.0.0, September 2023

4.0

3.14.1, January 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

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

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++

Server operating systems

hosted

Linux

All OS with a Java VM

BSD
Linux
OS X
Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

integer and binary

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

since Version 4.2

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
Java
Perl
Python
R

Java

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

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

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

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

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

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

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

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