DBMS > GridDB vs. MariaDB vs. Realm vs. Vertica

System Properties Comparison GridDB vs. MariaDB vs. Realm vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Key-value store
Relational DBMS

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

griddb.net

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

realm.io

www.vertica.com

Technical documentation

docs.griddb.net

mariadb.com/kb/en/library

realm.io/docs

vertica.com/documentation

Developer

Toshiba Corporation

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

The lead developer Monty Widenius is the original author of MySQL

Realm, acquired by MongoDB in May 2019

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2013

2009

Fork of MySQL, which was first released in 1995

2014

2005

Current release

5.1, August 2022

11.3.2, February 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and C++

C++

Server operating systems

Linux

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

yes

Dynamic columns are supported

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary extensions

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

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

Ada
C
C#
C++
D
Eiffel
Erlang
Go
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++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

PL/SQL compatibility added with version 10.3

runs within the applications so server-side scripts are unnecessary

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Change Listeners

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

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 at container level

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

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

In-Memory realm

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
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MariaDB is the most powerful open source relational database – modern SQL and JSON...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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MariaDB Servers have many features unavailable in other open source relational databases....
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
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Web, SaaS and Cloud operational applications that require high availability, scalability...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
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Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics

GitHub trending repository
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MariaDB is the default database in the LAMP stack supplied by Red Hat and SUSE Linux,...
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Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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MariaDB plc subscriptions cover our free, open source database, Community Server,...
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Cost-based models and subscription-based models are both available. One license is...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.