DBMS > Amazon CloudSearch vs. EsgynDB vs. GigaSpaces vs. Greenplum vs. Microsoft Azure Cosmos DB

System Properties Comparison Amazon CloudSearch vs. EsgynDB vs. GigaSpaces vs. Greenplum vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

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.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Search engine

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

aws.amazon.com/cloudsearch

www.esgyn.cn

www.gigaspaces.com

greenplum.org

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.gigaspaces.com/latest/landing.html

docs.greenplum.org

learn.microsoft.com/azure/cosmos-db

Developer

Amazon

Esgyn

Gigaspaces Technologies

Pivotal Software Inc.

Microsoft

Initial release

2012

2015

2000

2005

2014

Current release

15.5, September 2020

7.0.0, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

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++, Java

Java, C++, .Net

Server operating systems

hosted

Linux

Linux
macOS
Solaris
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

XML can be used for describing objects metadata

yes

since Version 4.2

Secondary indexes

yes

all search fields are automatically indexed

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-99 for query and DML statements

yes

SQL-like query language

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC

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

JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C++
Java
Python
Scala

C
Java
Perl
Python
R

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

JavaScript

Triggers

yes, event driven architecture

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Multi-source replication between multi datacenters

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

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

authentication via encrypted signatures

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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