DBMS > Dgraph vs. Drizzle vs. GridGain vs. Microsoft SQL Server vs. ToroDB

System Properties Comparison Dgraph vs. Drizzle vs. GridGain vs. Microsoft SQL Server vs. ToroDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed and scalable native Graph DBMS

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Microsofts flagship relational DBMS

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Graph DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

dgraph.io

www.gridgain.com

www.microsoft.com/en-us/sql-server

github.com/torodb/server

Technical documentation

dgraph.io/docs

www.gridgain.com/docs/index.html

learn.microsoft.com/en-US/sql/sql-server

Developer

Dgraph Labs, Inc.

Drizzle project, originally started by Brian Aker

GridGain Systems, Inc.

Microsoft

8Kdata

Initial release

2016

2008

2007

1989

2016

Current release

7.2.4, September 2012

GridGain 8.5.1

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

commercial

restricted free version is available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java, C++, .Net

C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Linux
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

yes

with proprietary extensions

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

yes

APIs and other access methods

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

JDBC

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

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

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

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

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication
Source-replica replication

yes (replicated cache)

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Planned for future releases

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Access rights for users and roles

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