DBMS > BigchainDB vs. GridGain vs. Microsoft Azure SQL Database vs. MySQL vs. Yaacomo

System Properties Comparison BigchainDB vs. GridGain vs. Microsoft Azure SQL Database vs. MySQL vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

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

Widely used open source RDBMS

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

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

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.bigchaindb.com

www.gridgain.com

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

www.mysql.com

yaacomo.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.gridgain.com/docs/index.html

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

dev.mysql.com/doc

Developer

GridGain Systems, Inc.

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Q2WEB GmbH

Initial release

2016

2007

2010

1995

2009

Current release

GridGain 8.5.1

V12

8.4.0, April 2024

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

Java, C++, .Net

C++

C and C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Android
Linux
Windows

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

with proprietary extensions

yes

APIs and other access methods

CLI Client
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

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

Server-side scripts

Stored procedures

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

Transact SQL

yes

proprietary syntax

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes (replicated cache)

yes, with always 3 replicas available

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

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,with MongoDB ord RethinkDB

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

yes

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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