DBMS > Amazon CloudSearch vs. Citus vs. GridGain vs. Memgraph vs. Microsoft Azure Cosmos DB

System Properties Comparison Amazon CloudSearch vs. Citus vs. GridGain vs. Memgraph 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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

GridGain is an in-memory computing platform, built on Apache Ignite

An open source graph database built for real-time streaming and compatible with Neo4j

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Search engine

Relational DBMS

Key-value store
Relational DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph 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.citusdata.com

www.gridgain.com

memgraph.com

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.citusdata.com

www.gridgain.com/docs/index.html

memgraph.com/docs

learn.microsoft.com/azure/cosmos-db

Social network pages

Developer

Amazon

GridGain Systems, Inc.

Memgraph Ltd

Microsoft

Initial release

2012

2010

2007

2017

2014

Current release

8.1, December 2018

GridGain 8.5.1

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

commercial

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

C and C++

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

Linux

hosted

Data scheme

yes

schema-free and schema-optional

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.

yes

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

standard, with numerous extensions

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

APIs and other access methods

HTTP API

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Bolt protocol
Cypher query language

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

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

user defined functions

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

yes (compute grid and cache interceptors can be used instead)

JavaScript

Triggers

yes

yes (cache interceptors and events)

JavaScript

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

dynamic graph partitioning

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Source-replica replication

other methods possible by using 3rd party extensions

yes (replicated cache)

Multi-source replication using RAFT

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

with snapshot isolation

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

Security Hooks for custom implementations

Users, roles and permissions

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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