DBMS > Amazon CloudSearch vs. Memgraph vs. PostgreSQL

System Properties Comparison Amazon CloudSearch vs. Memgraph vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

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

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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Search engine

Graph DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.64
Rank	#135	Overall
	#12	Search engines

Score	2.54
Rank	#98	Overall
	#8	Graph DBMS

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Website

aws.amazon.com/cloudsearch

memgraph.com

www.postgresql.org

Technical documentation

docs.aws.amazon.com/cloudsearch

memgraph.com/docs

www.postgresql.org/docs

Developer

Amazon

Memgraph Ltd

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2012

2017

1989

1989: Postgres, 1996: PostgreSQL

Current release

16.4, August 2024

License

Commercial or Open Source

commercial

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

Server operating systems

hosted

Linux

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

schema-free and schema-optional

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.

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

HTTP API

Bolt protocol
Cypher query language

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

Supported programming languages

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

.Net
C
C++
Delphi
Java

JDBC
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.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

dynamic graph partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Multi-source replication using RAFT

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

with snapshot isolation

ACID

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

Users, roles and permissions

fine grained access rights according to SQL-standard

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