DBMS > Amazon DynamoDB vs. EDB Postgres vs. GigaSpaces vs. HEAVY.AI vs. Postgres-XL

System Properties Comparison Amazon DynamoDB vs. EDB Postgres vs. GigaSpaces vs. HEAVY.AI vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

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

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Search engine

Spatial DBMS

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	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

aws.amazon.com/dynamodb

www.enterprisedb.com

www.gigaspaces.com

github.com/heavyai/heavydb
www.heavy.ai

www.postgres-xl.org

Technical documentation

docs.aws.amazon.com/dynamodb

www.enterprisedb.com/docs

docs.gigaspaces.com/latest/landing.html

docs.heavy.ai

www.postgres-xl.org/documentation

Developer

Amazon

EnterpriseDB

Gigaspaces Technologies

HEAVY.AI, Inc.

Initial release

2012

2005

2000

2016

2014

since 2012, originally named StormDB

Current release

14, December 2021

15.5, September 2020

5.10, January 2022

10 R1, October 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache Version 2; enterprise edition available

Open Source

Mozilla public license

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++, .Net

C++ and CUDA

Server operating systems

hosted

Linux
Windows

Linux
macOS
Solaris
Windows

Linux

Linux
macOS

Data scheme

schema-free

yes

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.

yes

specific XML-type available, but no XML query functionality.

XML can be used for describing objects metadata

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

SQL-99 for query and DML statements

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

.Net
C++
Java
Python
Scala

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

Sharding

Round robin

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

MVCC

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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)

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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