DBMS > GigaSpaces vs. HugeGraph vs. MariaDB vs. Vertica

System Properties Comparison GigaSpaces vs. HugeGraph vs. MariaDB vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

A fast-speed and highly-scalable Graph DBMS

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.

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

Document store
Object oriented DBMS

Values are user defined objects

Graph DBMS

Relational DBMS

Column oriented

Secondary database models

Graph DBMS
Search engine

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	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	91.04
Rank	#13	Overall
	#9	Relational DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

www.gigaspaces.com

github.com/hugegraph
hugegraph.apache.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.vertica.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

hugegraph.apache.org/docs

mariadb.com/kb/en/library

vertica.com/documentation

Developer

Gigaspaces Technologies

Baidu

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

The lead developer Monty Widenius is the original author of MySQL

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2000

2018

2009

Fork of MySQL, which was first released in 1995

2005

Current release

15.5, September 2020

0.9

11.3.2, February 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial enterprise subscription available

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.

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

Implementation language

Java, C++, .Net

Java

C and C++

C++

Server operating systems

Linux
macOS
Solaris
Windows

Linux
macOS
Unix

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux

Data scheme

schema-free

yes

Dynamic columns are supported

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

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

also supports composite index and range index

yes

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

SQL

Support of SQL

SQL-99 for query and DML statements

yes

with proprietary extensions

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

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Java API
RESTful HTTP API
TinkerPop Gremlin

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

.Net
C++
Java
Python
Scala

Groovy
Java
Python

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

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

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

yes

PL/SQL compatibility added with version 10.3

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, event driven architecture

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

several options for horizontal partitioning and Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication
Source-replica replication

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

yes

Map-Reduce pattern can be built with XAP task executors

via hugegraph-spark

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

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

User concepts

Access control

Role-based access control

Users, roles and permissions

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

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

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

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

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

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

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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