DBMS > Amazon Neptune vs. Drizzle vs. PostgreSQL vs. SurrealDB vs. Trino

System Properties Comparison Amazon Neptune vs. Drizzle vs. PostgreSQL vs. SurrealDB vs. Trino

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Fast, reliable graph database built for the cloud

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Widely used open source RDBMS

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

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

Document store
Graph DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	2.13
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Score	1.08
Rank	#176	Overall
	#30	Document stores
	#16	Graph DBMS

Score	5.34
Rank	#60	Overall
	#34	Relational DBMS

Website

aws.amazon.com/neptune

www.postgresql.org

surrealdb.com

trino.io

Technical documentation

aws.amazon.com/neptune/developer-resources

www.postgresql.org/docs

surrealdb.com/docs

trino.io/broadcast
trino.io/docs/current

Developer

Amazon

Drizzle project, originally started by Brian Aker

PostgreSQL Global Development Group

www.postgresql.org/developer

SurrealDB Ltd

Trino Software Foundation

Initial release

2017

2008

1989

1989: Postgres, 1996: PostgreSQL

2022

2012

2020 rebranded from PrestoSQL

Current release

7.2.4, September 2012

16.4, August 2024

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

BSD

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C++

Rust

Java

Server operating systems

hosted

FreeBSD
Linux
OS X

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

Linux
macOS
Windows

Linux
macOS

for devlopment

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.

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

with proprietary extensions

yes

standard with numerous extensions

SQL-like query language

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC

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

GraphQL
RESTful HTTP API
WebSocket

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C++
Java
PHP

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Deno
Go
JavaScript (Node.js)
Rust

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

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

yes, depending on connected data-source

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

depending on connected data-source

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

SQL standard access control

More information provided by the system vendor

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