DBMS > AllegroGraph vs. Amazon DynamoDB vs. Microsoft Azure Synapse Analytics vs. PlanetScale vs. Postgres-XL

System Properties Comparison AllegroGraph vs. Amazon DynamoDB vs. Microsoft Azure Synapse Analytics vs. PlanetScale vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

allegrograph.com

aws.amazon.com/dynamodb

azure.microsoft.com/services/synapse-analytics

planetscale.com

www.postgres-xl.org

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

docs.aws.amazon.com/dynamodb

docs.microsoft.com/azure/synapse-analytics

planetscale.com/docs

www.postgres-xl.org/documentation

Developer

Franz Inc.

Amazon

Microsoft

PlanetScale

Initial release

2004

2012

2016

2020

2014

since 2012, originally named StormDB

Current release

8.0, December 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

Limited community edition free

commercial

free tier for a limited amount of database operations

commercial

Open Source

Mozilla public license

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++

Server operating systems

Linux
OS X
Windows

hosted

Docker
Linux
macOS

Linux
macOS

Data scheme

yes

RDF schemas

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.

bulk load of XML files possible

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

with proprietary extensions

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API
SPARQL

RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

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

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Java
PHP

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Transact SQL

yes

proprietary syntax

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

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

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

ACID at shard level

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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

yes

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

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