DBMS > Amazon DynamoDB vs. HugeGraph vs. Microsoft Azure Synapse Analytics vs. Postgres-XL vs. RisingWave

System Properties Comparison Amazon DynamoDB vs. HugeGraph vs. Microsoft Azure Synapse Analytics vs. Postgres-XL vs. RisingWave

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

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

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

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Document store
Key-value store

Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

aws.amazon.com/dynamodb

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/services/synapse-analytics

www.postgres-xl.org

www.risingwave.com/database

Technical documentation

docs.aws.amazon.com/dynamodb

hugegraph.apache.org/docs

docs.microsoft.com/azure/synapse-analytics

www.postgres-xl.org/documentation

docs.risingwave.com/docs/current/intro

Developer

Amazon

Baidu

Microsoft

RisingWave Labs

Initial release

2012

2018

2016

2014

since 2012, originally named StormDB

2022

Current release

0.9

10 R1, October 2018

1.2, September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

Open Source

Mozilla public license

Open Source

Apache Version 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

Java

C++

Rust

Server operating systems

hosted

Linux
macOS
Unix

hosted

Linux
macOS

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

XML type, but no XML query functionality

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

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

JDBC
PostgreSQL wire protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Groovy
Java
Python

C#
Java
PHP

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Transact SQL

user defined functions

UDFs in Python or Java

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

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

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

Users, roles and permissions

yes

fine grained access rights according to SQL-standard

Users and Roles

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