DBMS > GridGain vs. Microsoft Azure Synapse Analytics vs. Percona Server for MySQL

System Properties Comparison GridGain vs. Microsoft Azure Synapse Analytics vs. Percona Server for MySQL

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Editorial information provided by DB-Engines

Name

Description

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

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

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Primary database model

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.53
Rank	#155	Overall
	#26	Key-value stores
	#73	Relational DBMS

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	2.21
Rank	#121	Overall
	#58	Relational DBMS

Website

www.gridgain.com

azure.microsoft.com/services/synapse-analytics

www.percona.com/software/mysql-database/percona-server

Technical documentation

www.gridgain.com/docs/index.html

docs.microsoft.com/azure/synapse-analytics

www.percona.com/downloads/Percona-Server-LATEST

Developer

GridGain Systems, Inc.

Microsoft

Percona

Initial release

2007

2016

2008

Current release

GridGain 8.5.1

8.0.36-28, 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2

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++

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

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

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

ADO.NET
JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java
PHP

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
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

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Multi-source replication
Source-replica replication
XtraDB Cluster

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

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

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

Security Hooks for custom implementations

yes

Users with fine-grained authorization concept

no user groups or roles

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More resources

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