DBMS > Amazon Neptune vs. EDB Postgres vs. Microsoft Azure Synapse Analytics vs. SAP Advantage Database Server vs. Spark SQL

System Properties Comparison Amazon Neptune vs. EDB Postgres vs. Microsoft Azure Synapse Analytics vs. SAP Advantage Database Server vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the 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.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Low-cost RDBMS with access to ISAM and FoxPro data structures

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.82
Rank	#108	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	2.06
Rank	#124	Overall
	#60	Relational DBMS

Score	20.66
Rank	#36	Overall
	#22	Relational DBMS

Score	3.68
Rank	#91	Overall
	#47	Relational DBMS

Score	22.86
Rank	#35	Overall
	#21	Relational DBMS

Website

aws.amazon.com/neptune

www.enterprisedb.com

azure.microsoft.com/services/synapse-analytics

www.sap.com/products/advantage-database-server.html

spark.apache.org/sql

Technical documentation

aws.amazon.com/neptune/developer-resources

www.enterprisedb.com/edb-docs

docs.microsoft.com/azure/synapse-analytics

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Amazon

EnterpriseDB

Microsoft

Sybase, SAP

Apache Software Foundation

Initial release

2017

2005

2016

1993

2014

Current release

14, December 2021

3.2.0, October 2021

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

commercial

Open Source

Apache 2.0

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++

Scala

Server operating systems

hosted

Linux
Windows

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

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

SQL

Support of SQL

yes

standard with numerous extensions

yes

SQL-like DML and DDL statements

APIs and other access methods

RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin 3.3

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

ADO.NET
JDBC
ODBC

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

C#
Java
PHP

Delphi
Perl
PHP

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

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

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

by hash, list or range

Sharding, horizontal partitioning

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas

Multi-source replication

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

caching of (temporary) tables can be configured

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

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

PostgreSQL with added Security, Performance, DBA, Developer, and Oracle compatibile...
» more

Competitive advantages

Complete Postgres platform with enterprise-class Postgres, Management, Integration,...
» more

Typical application scenarios

New applications for transactional, reporting and mixed workloads that need to integrate...
» more

Key customers

MasterCard, Hewlett Packard Enterprise, Ericsson, AT&T, Alibaba, Korea Telecom and...
» more

Market metrics

Listed in Gartner Magic Quadrant 2013-2018 with over 4,000 customers.
» more

Licensing and pricing models

Open Source and Commercial core based licensing.
» more

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