DBMS > Apache Phoenix vs. Dgraph vs. Greenplum vs. GridGain vs. Microsoft Azure SQL Database

System Properties Comparison Apache Phoenix vs. Dgraph vs. Greenplum vs. GridGain vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Distributed and scalable native Graph DBMS

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

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

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

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

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Website

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

Technical documentation

phoenix.apache.org

dgraph.io/docs

docs.greenplum.org

www.gridgain.com/docs/index.html

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

Developer

Apache Software Foundation

Dgraph Labs, Inc.

Pivotal Software Inc.

GridGain Systems, Inc.

Microsoft

Initial release

2014

2016

2005

2007

2010

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

7.0.0, September 2023

GridGain 8.5.1

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Java, C++, .Net

C++

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

yes

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

yes

APIs and other access methods

JDBC

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

JDBC
ODBC

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

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

C
Java
Perl
Python
R

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

user defined functions

yes

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

Transact SQL

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication via Raft

Source-replica replication

yes (replicated cache)

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Planned for future releases

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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More resources

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Recent citations in the news

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