DBMS > Amazon DynamoDB vs. Dgraph vs. GridGain vs. Microsoft Azure SQL Database vs. Microsoft Azure Synapse Analytics

System Properties Comparison Amazon DynamoDB vs. Dgraph vs. GridGain vs. Microsoft Azure SQL Database vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines

Name

Description

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

Distributed and scalable native Graph DBMS

GridGain is an in-memory computing platform, built on Apache Ignite

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Primary database model

Document store
Key-value store

Graph DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
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	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

aws.amazon.com/dynamodb

dgraph.io

www.gridgain.com

azure.microsoft.com/en-us/products/azure-sql/database

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.aws.amazon.com/dynamodb

dgraph.io/docs

www.gridgain.com/docs/index.html

docs.microsoft.com/en-us/azure/azure-sql

docs.microsoft.com/azure/synapse-analytics

Developer

Amazon

Dgraph Labs, Inc.

GridGain Systems, Inc.

Microsoft

Initial release

2012

2016

2007

2010

2016

Current release

GridGain 8.5.1

V12

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

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++, .Net

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

hosted

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

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
Java
PHP

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Transact SQL

Triggers

yes

by integration with AWS Lambda

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

yes (replicated cache)

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

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)

Planned for future releases

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

yes

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