DBMS > GridGain vs. MySQL vs. Realm vs. SAP SQL Anywhere vs. Sphinx

System Properties Comparison GridGain vs. MySQL vs. Realm vs. SAP SQL Anywhere vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Relational DBMS

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

www.gridgain.com

www.mysql.com

realm.io

www.sap.com/products/technology-platform/sql-anywhere.html

sphinxsearch.com

Technical documentation

www.gridgain.com/docs/index.html

dev.mysql.com/doc

realm.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

sphinxsearch.com/docs

Developer

GridGain Systems, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Realm, acquired by MongoDB in May 2019

SAP

formerly Sybase

Sphinx Technologies Inc.

Initial release

2007

1995

2014

1992

2001

Current release

GridGain 8.5.1

9.0.0, July 2024

17, July 2015

3.5.1, February 2023

License

Commercial or Open Source

commercial, open source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net, Python, REST, SQL

C and C++

C++

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

FreeBSD
Linux
OS X
Solaris
Windows

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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

full-text index on all search fields

SQL

Support of SQL

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

yes

with proprietary extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

.Net
Java

with Android only
Objective-C
React Native
Swift

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

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

yes

proprietary syntax

runs within the applications so server-side scripts are unnecessary

yes, in C/C++, Java, .Net or Perl

Triggers

yes (cache interceptors and events)

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication
Source-replica replication

none

Source-replica replication

Database mirroring

none

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

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-Memory realm

yes

User concepts

Access control

Role-based access control
Security Hooks for custom implementations

Users with fine-grained authorization concept

no user groups or roles

yes

fine grained access rights according to SQL-standard

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