DBMS > Hive vs. Informix vs. MariaDB vs. Pinecone

System Properties Comparison Hive vs. Informix vs. MariaDB vs. Pinecone

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things 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 managed, cloud-native vector database

Primary database model

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	17.87
Rank	#35	Overall
	#22	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

hive.apache.org

www.ibm.com/products/informix

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.pinecone.io

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

mariadb.com/kb/en/library

docs.pinecone.io/docs/overview

Developer

Apache Software Foundation

initially developed by Facebook

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

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

The lead developer Monty Widenius is the original author of MySQL

Pinecone Systems, Inc

Initial release

2012

1984

2009

Fork of MySQL, which was first released in 1995

2019

Current release

3.1.3, April 2022

14.10.FC5, November 2020

11.3.2, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free developer edition available

Open Source

GPL version 2, commercial enterprise subscription available

commercial

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, C++ and Java

C and C++

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

hosted

Data scheme

yes

Dynamic columns are supported

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

yes

String, Number, Boolean

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

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Supported programming languages

C++
Java
PHP
Python

.Net
C
C++
Java
JavaScript (Node.js)
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

Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

Access rights for users, groups and roles

Users with fine-grained authentication, authorization, and auditing controls

fine grained access rights according to SQL-standard

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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Competitive advantages

MariaDB Servers have many features unavailable in other open source relational databases....
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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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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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