DBMS > GridGain vs. H2GIS vs. MariaDB vs. Solr vs. SQream DB

System Properties Comparison GridGain vs. H2GIS vs. MariaDB vs. Solr vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

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

Spatial extension of H2

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

A widely used distributed, scalable search engine based on Apache Lucene

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Key-value store
Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Spatial DBMS

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

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

www.gridgain.com

www.h2gis.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

solr.apache.org

sqream.com

Technical documentation

www.gridgain.com/docs/index.html

www.h2gis.org/docs/home

mariadb.com/kb/en/library

solr.apache.org/resources.html

docs.sqream.com

Developer

GridGain Systems, Inc.

CNRS

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Apache Software Foundation

SQream Technologies

Initial release

2007

2013

2009

Fork of MySQL, which was first released in 1995

2006

2017

Current release

GridGain 8.5.1

11.3.2, February 2024

9.6.0, April 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

Apache Version 2

commercial

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.

STACKIT MariaDB offers MariaDB in a fully managed version in enterprise grade, 100% GDPR-compliant.

Implementation language

Java, C++, .Net

Java

C and C++

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
OS X
Solaris
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

yes

Dynamic columns are supported

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

yes, ANSI Standard SQL Types

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

All search fields are automatically indexed

SQL

Support of SQL

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

yes

with proprietary extensions

Solr Parallel SQL Interface

yes

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

Java API
RESTful HTTP/JSON API

.Net
JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Java

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

yes

based on H2

yes

PL/SQL compatibility added with version 10.3

Java plugins

user defined functions in Python

Triggers

yes (cache interceptors and events)

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

several options for horizontal partitioning and Sharding

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

based on H2

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

In-memory capabilities

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

yes

with MEMORY storage engine

yes

User concepts

Access control

Security Hooks for custom implementations

yes

based on H2

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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